Search Results (18,733)

Distributed cloud networks spanning multiple jurisdictions face significant challenges in anomaly detection due to privacy constraints, regulatory requirements, and communication limitations. This paper presents a mathematically rigorous framework for privacy-preserving federated learning on hierarchical graph neural networks, providing theoretical convergence guarantees and optimisation bounds for distributed anomaly detection. A novel layer-wise federated aggregation mechanism is introduced, featuring a proven convergence rate $O\left(1/\sqrt{T}\right)$. That preserves hierarchical structure during distributed training. The theoretical analysis establishes differential privacy guarantees of $\left(\epsilon =1.0, \delta ={10}^{-5}\right)$ through layer-specific noise calibration, achieving optimal privacy–utility tradeoffs. The proposed optimisation framework incorporates: (1) convergence-guaranteed layer-wise aggregation with bounded gradient norms, (2) privacy-preserving mechanisms with formal composition analysis under the Moments Accountant framework, (3) meta-learning-based personalisation with theoretical generalisation bounds, and (4) communication-efficient protocols with a proven 93% reduction in overhead. Rigorous evaluation on the FEDGEN testbed, spanning 2780 km across Nigeria and the Democratic Republic of Congo, demonstrates superior performance with hierarchical F1-scores exceeding 95% across all regions, while maintaining theoretical guarantees. The framework’s convergence analysis shows robustness under realistic constraints, including 67% client participation, 200 ms latency, and 20 Mbps bandwidth limitations. This work advances the theoretical foundations of federated graph learning while providing practical deployment guidelines for cross-jurisdictional cloud networks. Full article

This study investigates the impact of cattle breed on key quality attributes—color, marbling, and tenderness—central to consumer choice. Six different bovine breeds were taken into consideration: German Red Pied, Piemontese, Chianina, Angus, Holstein, and a Polish crossbreed. The muscle taken into consideration was the Longissimus thoracis et lumborum. Colorimetric assessments, marbling evaluations, fatty acid profiling, and tenderness measurements were conducted on meat cuts from each breed. The results revealed that Chianina, Holstein, and the Polish crossbreed exhibited distinct color characteristics, with Chianina displaying notably brighter meat. Angus emerged as the most marbled breed, while Chianina and Piemontese showed lower marbling. Total lipid content was correlated with visible marbling. Tenderness assessments identified Angus and Holstein as the most tender breeds. The study’s findings contribute to a proposed grading scale for color, marbling, and tenderness, offering potential labeling infographics to assist consumers in making informed choices based on individual preferences and needs. These insights underscore the importance of breed-specific information on labels to enhance consumer understanding and facilitate more informed purchasing decisions. Full article

Small- and medium-sized enterprises (SMEs) are increasingly embracing digital transformation (DT) to remain competitive; however, the enabling role of knowledge management (KM) remains underexplored. This systematic literature review investigates how KM supports DT in SMEs, focusing on strategic processes, tools, barriers, and policy contexts. A structured search was conducted in Google Scholar, Scopus, and Web of Science using the string: (“knowledge management” OR “KM”) AND (“digital transformation” OR “DT”) AND (“small and medium enterprises” OR “SME”). The search yielded 32,547 results, from which 19 studies met the eligibility criteria (English, 2020–2025, KM–DT focus, clear methodology). Results indicate that KM supports DT primarily through change management (31.58%), innovation enablement (21.05%), as well as improved decision-making and agility (15.79%). The most cited tools include KM systems, AI/analytics, and collaborative platforms. Major barriers include limited resources, lack of digital skills, and poor KM culture. Critical success factors identified are leadership commitment (26.32%) and strategic alignment (21.05%). Theoretical foundations are dominated by the Resource-Based View and Dynamic Capabilities Theory. While KM is proven to be a strategic driver of DT in SMEs, more empirical and policy-grounded studies are needed. This review provides a framework to guide future research and inform SME practitioners and policymakers. Full article

Using a time-frequency and quantile connectedness approach, our study examines the complex return spillovers dynamics between BRICS Plus stock markets, the volatility index (VIX), and the global geopolitical risk index (GPRD). By employing advanced models such as TVP-VAR, quantile connectedness, and spectral decomposition, we demonstrate how these markets interact across different market conditions and periods. Our results indicate that the VIX consistently acts as the dominant net transmitter of shocks, especially during periods of heightened uncertainty such as the COVID-19 pandemic, the Russian-Ukraine conflict, and the Trump-era U.S.-China trade tensions. In contrast, the GPRD functions predominantly as a net receiver of shocks, indicating its potential role as a hedge during geopolitical crises. BRICS Plus markets exhibit heterogeneous behavior: Brazil, South Africa, and Russia frequently emerge as net transmitters, while China, India, Egypt, Saudi Arabia, and the UAE primarily act as net receivers. Spillovers are strongest at the extremes of the return distribution and are mainly driven by short-term dynamics, underscoring the importance of high-frequency reactions over persistent long-term effects. These findings highlight the asymmetric, nonlinear, and state-dependent nature of global financial contagion, offering important insights for risk management, asset allocation, and macroprudential policy design in emerging market contexts. Full article

While extensive research has explored the determinants of foreign direct investment (FDI) and foreign portfolio investment (FPI) in BRICS nations, there remains a notable gap in understanding the influence of intangible factors, particularly soft power and nation branding. Historically, academic discourse has underemphasized the role of nation branding as a crucial emotional and perceptual component in investment decision-making processes. Consequently, governments in BRICS countries must enhance their national branding efforts to attract both capital and portfolio investment flows. The principal aim of this study was to jointly analyse the tangible and intangible determinants influencing FDI and FPI in BRICS from 1994 to 2024. Employing advanced econometric techniques, specifically the Autoregressive Distributed Lag (ARDL) bounds testing approach for cointegration and Vector Error Correction Models (VECM) for estimation. This study makes a unique contribution to existing literature by examining the nexus between nation branding, FDI and FPI, thereby introducing a novel perspective on the factors driving investment in the BRICS context with an emphasis on non-tangible determinants. The findings indicate that nation branding, along with exchange rate stability, property rights, and financial market development, are significant positive determinants of FPI in these countries. Conversely, capital openness demonstrated a negative relationship with FPI. Moreover, the positive impact of nation branding on FDI within BRICS nations was reaffirmed. This study substantiates the critical role of nation branding as a pivotal driver for both FDI and FPI, emphasising its strategic importance in the economic landscape of BRICS countries. Full article

South Africa has relatively recently transitioned from a condition of legislated racial stratification to a democracy in which all South Africans now enjoy political enfranchisement. While political emancipation has been achieved, economic and social emancipation remain elusive for the majority of Black South Africans who still bear the brunt of poverty and deprivation. South Africa’s white colonial communities, having relinquished political power, continue to retain and enjoy economic and social class privileges. Despite state-driven social cohesion and nation-building initiatives, the envisaged ‘rainbow nation’ (a metaphor coined by the late Archbishop Desmond Tutu) is becoming an increasingly fragile social aspiration. Historical legacies, especially regarding white affirmation, wealth accumulation, and the imperative for economic redistribution and land reform, have become key flashpoints in contemporary South Africa. This paper addresses the issue of how South Africa’s corrective justice and affirmative action policies are re-racialised into narratives of reverse racism, white persecution, and white genocide. It examines how racial arbitrage works where whiteness is systematically re-racialised and traded for its value in a different country context. It examines how disillusioned white South Africans leverage white racial and class privilege for transnational mobility and protections, white settler-colonial receptivity and white nationhood. It draws attention to the tensions and contradictions in global asylum regimes, illuminating transnational networks of privilege and economic superpower coercion. Full article

Background/Objectives: HIV-exposed uninfected (HEU) infants experience increased severe respiratory syncytial virus lower respiratory tract illness (RSV-LRTI) rates compared with HIV-unexposed infants. Maternal bivalent RSVpreF vaccination can prevent infant RSV-LRTI but data from HEU infants are lacking. Methods: This phase 3 randomized, double-blinded trial assessed RSVpreF safety and immunogenicity in pregnant participants from South Africa living with HIV and their infants. Maternal participants with stable HIV disease taking antiretroviral therapy received RSVpreF or placebo (24–36 weeks’ gestation). Primary safety endpoints included reactogenicity through 7 days after vaccination (maternal participants), adverse events (AEs) through 1 month after vaccination (maternal participants) or birth (infants), and serious AEs (SAEs) throughout the study (maternal participants) or through 6 months after birth (infants). Immune responses were evaluated by 50% RSV-A and RSV-B neutralizing titers prevaccination and at delivery (maternal participants) or birth (infants). Results: Overall, 343 maternal participants received RSVpreF (n = 172) or placebo (n = 171). Most reactogenicity events were mild/moderate. AEs and SAEs were generally reported at similar frequencies in maternal RSVpreF and placebo groups including percentages of hypertensive disorders of pregnancy. There were no safety concerns in infants; percentages of reported AEs and SAEs were generally similar between RSVpreF and placebo groups and no difference in preterm birth. RSVpreF elicited high maternal neutralizing RSV-A and RSV-B immune responses, with efficient RSV antibody transplacental transfer to infants demonstrated by levels greater than the placebo group at birth (geometric mean ratios (GMRs) of RSVpreF to placebo were 7.8 for RSV-A and 6.8 for RSV-B) and by comparison with a cohort of HIV-unexposed infants from the pivotal phase 3 efficacy trial (GMRs of HEU to HIV-unexposed infants were 0.86 for RSV-A and 0.72 for RSV-B). Conclusions: These results support maternal RSVpreF vaccination among those living with stable HIV for preventing RSV-LRTI in HEU infants. (NCT06325657). Full article

This paper presents a macroeconomic approach to calculating Climate Value-at-Risk (CliVaR) for financial institutions, addressing critical limitations in existing commercial solutions and historical data availability. This methodology leverages the Network for Greening the Financial System (NGFS) scenarios to derive implied forward-looking means and volatilities from scenarios mapped to macroeconomic variables (MEVs), circumventing the reliance on insufficient historical data. Through regression analysis, we identify statistically significant relationships between climate-sensitive macroeconomic variables and bank equity values, based on the premise that climate risk is transmitted to bank balance sheets via its impact on the general economy. It is recognised that MEVs alone cannot explain the full variance in equity values and the regression of MEVs to equity is inherently inefficient. However, the purpose of the regression is to determine statistically significant MEVs and not to predict the share price. Along with the NGFS scenarios, this enables the Monte Carlo simulation and the calculation of CliVaR. To account for the regression inefficiency, a Post-Model Adjustment (PMA) equation is developed. The methodology is demonstrated in a practical case study, by calculating a CliVaR based climate risk Pillar 2A capital requirement for Standard Bank Group. This proof-of-concept demonstrates the feasibility of transparent, in-house CliVaR calculations. Full article

Graph neural networks (GNNs) extend deep learning to non-Euclidean domains, offering a robust framework for modeling the spatial, structural, and functional relationships inherent in medical imaging. This paper reviews recent progress in GNN architectures, including recurrent, convolutional, attention-based, autoencoding, and spatiotemporal designs, and examines how these models have been applied to core medical imaging tasks, such as segmentation, classification, registration, reconstruction, and multimodal fusion. The review further identifies current challenges and limitations in applying GNNs to medical imaging and discusses emerging trends, including graph–transformer integration, self-supervised graph learning, and federated GNNs. This paper provides a concise and comprehensive reference for advancing reliable and generalizable GNN-based medical imaging systems. Full article

The rapid integration of wind power plants (WPPs) into modern electrical power systems (MEPSs) is crucial to global decarbonization, but it introduces significant technical challenges. Variability, intermittency, and forecasting uncertainty compromise frequency stability, voltage regulation, and grid reliability, particularly at high levels of renewable energy integration. To address these issues, adaptive control strategies have been proposed at the turbine, plant, and system levels, including reinforcement learning-based optimization, cooperative plant-level dispatch, and hybrid energy schemes with battery energy storage systems (BESS). At the same time, interoperability frameworks based on international standards, notably IEC 61850 and IEC 61400-25, provide the communication backbone for vendor-independent coordination; however, their application remains largely limited to monitoring and protection, rather than holistic adaptive operation. Real-Time Automation Controllers (RTACs) emerge as promising platforms for unifying monitoring, operation, and protection functions, but their deployment in large-scale WPPs remains underexplored. Validation of these frameworks is still dominated by simulation-only studies, while real-time digital simulation (RTDS) and hardware-in-the-loop (HIL) environments have only recently begun to bridge the gap between theory and practice. This review consolidates advances in adaptive control, interoperability, and validation, identifies critical gaps, including limited PCC-level integration, underutilization of IEC standards, and insufficient cyber–physical resilience, and outlines future research directions. Emphasis is placed on holistic adaptive frameworks, IEC–RTAC integration, digital twin–HIL environments, and AI-enabled adaptive methods with embedded cybersecurity. By synthesizing these perspectives, the review highlights pathways toward resilient, secure, and standards-compliant renewable power systems that can support the transition to a low-carbon future. Full article

Academic libraries have assumed expansive research data management (RDM) responsibilities, yet persistent dataset underutilisation suggests systemic disconnects between services and researcher needs. This scoping review applied a three-dimensional diagnostic framework to examine why libraries struggle to advance beyond consultative roles despite sustained investment. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines, this review analysed 34 empirical studies (2015–2025). Electronic databases, key journals, and grey literature sources were systematically reviewed, with 65% of studies originating from high-income (Global North) contexts. The analysis integrated the Institutional Readiness Index (IRI), Service Maturity Level (SML), and Information Flow Efficiency (IFE) to assess library engagement with research datasets. Three structural patterns constrain effectiveness. First, a capacity-complexity mismatch emerges as libraries manage increasingly diverse datasets without proportional infrastructure scaling, creating bottlenecks in discoverability, interoperability, and preservation. Second, structural progression barriers appear, where advancement requires simultaneous development across infrastructure, staffing, governance, and engagement rather than sequential improvement. Third, an implementation gap separates Findable, Accessible, Interoperable, Reusable (FAIR) policy awareness from operational capacity, as most institutions demonstrate standards knowledge without technical operationalisation ability. These patterns form interdependent constraints: infrastructure limitations correlate with restricted services, which are associated with persistent researcher skill gaps, reduced engagement, and constrained resource allocation, reinforcing the initial deficits. The review framework provides diagnostic specificity for identifying whether constraints stem from readiness, maturity, or implementation failures. This study advances RDM scholarship by explaining stagnation patterns rather than cataloguing services, offering an empirically grounded diagnostic tool. However, the findings reflect predominantly high-resource contexts and require validation across diverse institutional settings. Full article

Electronic communication and industrial protocols are critical to the reliable operation of modern electrical grids and Distributed Energy Resources (DERs). Communication loss between devices in renewable power plants can lead to significant revenue losses and jeopardize operational safety. While current control and automation systems for renewable plants are primarily based on the IEC 61131-3 standard, it lacks defined communication frameworks, leading most deployments to depend on Original Equipment Manufacturer (OEM)-specific protocols. The IEC 61499 standard, in contrast, offers a reference model for distributed automation systems, introducing Service Interface Function Blocks (SIFBs) and high-level communication abstractions that enable hardware-independent integration. This study proposes adopting the IEC 61499 standard for DER automation systems to enhance interoperability and flexibility among plant components. A photovoltaic power plant gateway is developed on a virtualized platform using open-source tools and libraries, including Python version 3, libmodbus version 3.1.7, and open62541 version 1 The implemented gateway successfully interfaces with industry-validated software applications, including UAExpert and Matrikon OPC Unified Architecture (OPC UA) clients, demonstrating the feasibility and effectiveness of IEC 61499-based integration in DER environments. Full article

This paper aims to explore the numerical solution of non-linear fractional-order Burgers’-Huxley equation based on Caputo’s formulation of fractional derivatives. The equation serves as a versatile tool for analyzing a wide range of physical, biological, and engineering systems, facilitating valuable insights into nonlinear dynamic phenomena. The fractional operator provides a comprehensive mathematical framework that effectively captures the non-locality, hereditary characteristics, and memory effects of various complex systems. The approximation of temporal differential operator is carried out through finite difference based L1 scheme, while spatial discretization is performed using modified cubic B-spline basis functions. The stability as well as convergence analysis of the approach are also presented. Additionally, some numerical test experiments are conducted to evaluate the computational efficiency of a modified fourth-order cubic B-spline (M43BS) approach. Finally, the results presented in the form of tables and graphs highlight the applicability and robustness of M43BS technique in solving fractional-order differential equations. The proposed methodology is preferred for its flexible nature, high accuracy, ease of implementation and the fact that it does not require unnecessary integration of weight functions, unlike other numerical methods such as Galerkin and spectral methods. Full article

There have been few reports of neoplasia in kangaroos to date. In this report, we describe a 13-year-old male captive Red kangaroo (Osphranter rufus) that developed a mass on the right side of the cloacal aperture. Histopathological analysis of a biopsy of the mass revealed proliferating, neoplastic epithelial islands with necrotic centres infiltrating a moderately desmoplastic dermis. The islands were generally large with extensive central caseation necrosis consisting of cellular debris and innumerable neutrophils. The neoplastic epithelial cells resembled the basal cells observed in the basal layer of the epidermis and were characterised by scant to moderate eosinophilic cytoplasm with indistinct cytoplasmic margins. The diagnosis was basal cell carcinoma (BCC). This is the first report of a BCC in a kangaroo, and we compare the findings with that seen in dogs, cats and humans. Full article