Synergy University Dubai

The pace of financial innovation in the Australian retail credit sector is ongoing, as is pressure on existing regulation. While new legislative and prudential regulatory measures are designed to address such pressure, there has been little consideration given to how such regulatory changes address the issue of systemic risk emanating from operational business associated with new products. This paper examines the role of complaints as a mechanism to uncover systemic risk in the Australian retail credit sector. Drawing on qualitative content analysis of sector complaints institutional reports for the period 2021-2025, the paper details the extent to which operational failures recur within complaint fields as an identifiable risk rather than as part of a formal regulatory preventative framework. The governance themes that emerge from the complaints institutional reports include containing complaints within the firm’s boundaries, customer stress in hardship reviews, system level policy divergences. The sequence in which firms respond to customer complaints. The author argues that the metaphoric of detection drift captures the shift in the sector from formal preventative regulation to the occurrence of complaint escalation and thus risk discovery. While using complaints for risk discovery affords the regulator some ‘risk-based learning’, it has the effect of producing a significant amount of detection drift (i.e. delays, uneven levels of detection and exposure to risk). To redress this risk, the author argues that there is a need for better integration of complaints, data analytics with on the ground prudential regulation and firm wide governance arrangements to ensure the ongoing stability of the retail credit sector in the face of financial innovation.

The interplay between magnetic order, charge dynamics, and crystal field excitations underpins the emergent ground states of rare-earth intermetallics. Using time-domain terahertz spectroscopy, we probe this coupling in PrSi, a metallic ferromagnet. The optical response exhibits pronounced Drude-Smith behavior over a broad temperature range, indicating persistent carrier scattering. A classical Kondo-lattice model (CKLM) attributes this non-Drude conductivity to scattering of itinerant electrons by localized magnetic moments, persisting down to temperatures well below the magnetic ordering scale. At lower temperatures, beyond the scope of CKLM, our experiment reveals that the response is dominated by crystal field excitations, with sharp transitions at 0.6 and 1.54THz. The mode at 1.54THz shows a dynamic correlation with the onset of ferromagnetic order, marking the onset of a crystal-field-governed low temperatureregime.

The Indian dairy sector is a vital industry experiencing significant transformation due to innovation, increased brand competition, new entrants, and retail evolution. A resource-informed roadmap is crucial for guiding investors, marketers, and policymakers in capitalising on opportunities in this dynamic landscape. In this regard, the current study aims to provide a roadmap for the traditional Indian cooperatives. It utilises comprehensive trend and forecasting analysis of the Indian dairy market. By leveraging data on brand share, company share, retail channels, and product ingredients used, the current study employs multiple models to examine the growth patterns of market leaders and emerging players. The study also includes growth analysis of the emerging hypermarket format in retail and market shares of various products. The best-fitting model is validated using residual analysis and cross-validation techniques. The study reveals that emerging players exhibit unstable yet aggressive growth, indicating their potential for disruption. The hypermarket assessment shows the retail industry's robust linear growth. This study employs the comprehensive GE-Matrix to analyse the strategic positioning of various players. Its novelty lies in integrating different model confidences into the strategic GE Matrix concerning the Indian dairy market. The findings suggest that traditional market players must innovate to maintain their stable growth, while investors must address and understand the challenges posed by the aggressive growth of emerging players. This research provides comprehensive data analysis, predictive insights into future trends, and strategic guidance for traditional market players in the Indian dairy industry.

Abstract Fine-tuning electrospun nanofibers is crucial for producing high-quality fibers. Taguchi Design of Experiment (DOE), along with various other computational techniques, has been used to optimize the electrospinning parameters of different polymers. Taguchi DOE has proven effective in optimizing electrospun nanofibers because it reduces the number of trials needed. In this study, the electrospinning parameters of poly (butylene adipate-co-terephthalate) (PBAT) were optimized and quantified using the Taguchi-based Response Surface Methodology (RSM) approach. The average fiber diameters were measured from Field Emission Scanning Electron Microscopy (FESEM) images using ImageJ software. Within the tested range of parameters and levels, the Analysis of Variance (ANOVA) study identified polymer concentration and flow rate as the most significant factors that influenced the fiber diameter. Polymer concentration accounting 56.94% of the variation, while Flow Rate (FR) accounts for 20.82%. The optimal parameter levels were predicted to be 10 wt.% polymer concentration, 1 mL/h flow rate, 18 kV voltage, and a distance from tip to target of 15cm, which yielded fibers with an average diameter of 231 nm and an accuracy of 88.61%. Overall, the results demonstrate that Taguchi DOE, coupled with RSM, is a reliable and efficient method for identifying the optimal parameter combinations to produce uniform, fine PBAT nanofibers intended for biomedical applications.

Black holes, traditionally studied as solutions of Einstein's equations, exhibit rich thermodynamic behavior, including well-defined phase transitions. In this work, we establish a unified topological framework to describe various black hole phase transitions, including Davies-type and extremal phase transitions. Our approach reveals a deeper underlying structure in black hole thermodynamics, demonstrating that these seemingly distinct transitions can be connected through topology. Furthermore, we show that the classification of phase transitions can be enriched by the introduction of non-zero topological charges, offering a novel perspective beyond conventional thermodynamic analysis. These findings not only strengthen the thermodynamic interpretation of black holes but also open new avenues for exploring phase transitions in gravitational systems from a topological standpoint.

The convergence of communication networks and power systems has transformed traditional grids into intelligent, interconnected smart grids. However, this integration exposes critical communication infrastructures to diverse cyber threats that can disrupt control and stability. This paper presents a Resilient Smart Grid Communication Analysis (RSGCA) framework designed to ensure secure and reliable operation under cyberattacks such as Denial-of-Service (DoS), Man-in-the-Middle (MITM), and False Data Injection (FDIA). The proposed framework integrates Software-Defined Networking (SDN) for adaptive routing, multi-agent coordination for distributed decision-making, and a hybrid Autoencoder-Trust intrusion detection model for intelligent anomaly detection. The approach is implemented and validated using OMNeT++ cosimulation to evaluate communication resilience and adaptive recovery under dynamic threat scenarios. The findings highlight that combining SDN programmability with intelligent, trustbased detection significantly enhances the security, adaptability, and resilience of next-generation smart grid communication infrastructures.

ObjectiveThis study aimed to compare the postoperative dry eye parameters following anterior lamellar recession without tarsal fracture versus tarsal fracture with marginal rotation in patients treated for cicatricial entropion.MethodsThis retrospective cohort study included adult patients diagnosed with primary or recurrent cicatricial entropion who underwent either anterior lamellar recession without tarsal fracture or tarsal fracture with marginal rotation. A comprehensive ocular assessment was performed pre- and postoperatively, including evaluation of tear film meniscus level, tear break-up time (TBUT), corneal fluorescein staining, Schirmer test, and Ocular Surface Disease Index (OSDI) questionnaire. In addition, the recurrence of entropion and associated symptoms was assessed.ResultsA total of 50 eyes were included in the study. Group A consisted of 25 patients who underwent anterior lamellar recession without tarsal fracture, with a mean age of 59.2±5.1 years. Group B consisted of 25 patients who underwent marginal rotation with tarsal fracture, with a mean age of 59.3±5.0 years. Both groups showed different degrees of deterioration of tear film stability after surgery. Group A showed significantly better results regarding the tear film meniscus level (p<0.001), TBUT (p=0.009), and OSDI (p=0.002) compared to group B. Meanwhile, the two groups were comparable regarding the recurrence rate (p=0.384).ConclusionBoth procedures have a comparable success rate. However, anterior lamellar recession without tarsal fracture is associated with better results in terms of tear film stability and quality in the postoperative period.

With the rapid pace of urbanization and the subsequent dominance of private vehicle usage, cities are under increasing pressure to offer sustainable alternatives to public transportation. Demand-responsive transport (DRT) systems provide flexible, technology-enabled services that bridge first- and last-mile connectivity gaps. This study assesses the operational and financial viability of Dubai's Bus-on-Demand (DBOD) service using Daganzo's continuum approximation framework, calibrated with empirical data from two service areas in Dubai. From the agency perspective, the Alternating Priorities routing strategy (i.e., alternating between nearest pickup and drop-off) was identified as optimal, balancing distance optimization with service consistency and contributing to shorter travel and waiting times. Cost efficiency is highest in compact service areas with moderate demand, with optimal vehicle occupancy of 10–15 passengers to minimize agency costs. To incorporate the user perspective, value of time (VOT) was calibrated for DBOD and integrated with agency costs. Based on the calibrated VOT, fleet size and operational parameters were optimized within a system framework. Moreover, a comparative analysis of three routing strategies across occupancy levels confirmed the superior cost-effectiveness of the Alternating Priorities approach, as implemented in DBOD. The study recommends that transit agencies refine vehicle dispatching, routing, and scheduling strategies to achieve optimal occupancy levels, and emphasizes the necessity of balancing agency and user costs for sustainable DRT implementation. These findings provide transit agencies with an empirical, data-driven framework to evaluate and optimize DRT services, supporting informed decision-making for sustainable urban mobility.