Ransomware groups pose a threat to both the economy and national security, yet little is known about their structural dynamics. This study analyses the Conti group using leaked Jabber encrypted instant messaging chat data (similar to Messenger) and Relational Event Models to examine how preferential attachment and triadic closure mechanisms shape its communication network. Findings show Conti prioritised efficiency through centralisation but mitigated risks via compartmentalisation, creating a hybrid structure that balances speed and secrecy. This adaptive approach enhances both effectiveness and resilience. The research provides new insights into the evolution of ransomware groups and suggests that disruption strategies should target internal cohesion rather than external infrastructure.
Objectives This study aimed to evaluate the technical feasibility of routine distributional analyses of healthcare interventions in Australia, by adapting a Health Inequality Impact Calculator for Queensland. Building on methods established in a previous study in England, the calculator compares the magnitude of health inequality impact across interventions for different diseases. Methods The calculator was adapted for adults in Queensland using the Index of Relative Socio-economic Advantage and Disadvantage quintiles, Australian Bureau of Statistics population estimates, 2023 hospital admissions (International Classification of Diseases-10th edition 3-digit level) from Queensland Health, and published quality-adjusted life expectancy. It was used to conduct aggregate distributional cost-effectiveness analysis of 5 interventions for diseases with relatively high prevalence in disadvantaged groups, based on existing cost-effectiveness results identified by a targeted review. The health inequality impact was summarized using the slope index of inequality in quality-adjusted life-years (QALYs). Results The selected interventions were 2 screening interventions for diabetes and hypertension, and 3 treatment interventions for chronic kidney disease. The calculator demonstrated that all 5 interventions would reduce health inequality. Population screening for diabetes had the greatest impact on reducing health inequality of 8562 QALYs. Among the 3 treatment interventions, intensive blood pressure control had the greatest impact, with a health inequality benefit of 514 QALYs. Conclusions Routine aggregate distributional cost-effectiveness analysis of interventions in Queensland is feasible, once standard cost-effectiveness estimates are available. The calculator for Queensland enables fast, transparent, and replicable analysis of health inequality impacts using minimal data, with visual outputs to explore trade-offs between health outcomes, inequality, and cost-effectiveness.
The Monash-Peradeniya-Kodikara (MPK) framework interprets the volumetric behaviour of compacted unsaturated soils in the void ratio - moisture ratio - net stress (e - ew -p) space without requiring suction as an independent constitutive variable. Nevertheless, explicit knowledge of suction distributions within this volumetric space can provide additional insight into hydromechanical behaviour and facilitate comparison with conventional suction-based frameworks. This paper reconstructs continuous suction surfaces on and inside the Loading Wetting State Boundary Surface (LWSBS) within the MPK space by combining suction topology inferred from published experimental datasets with a constrained mathematical reconstruction methodology consistent with MPK principles. The reconstruction is divided into three regions relative to the Line of Optimums (LOO). At the wet side of the LOO, suction contours on the LWSBS are reconstructed using effective stress relationships and semilogarithmic compression relationships. At the dry side of the LOO, suction contours are reconstructed from Soil Water Characteristic Curves (SWCCs) extended towards the dry condition using cubic Bezier curves. Suction contours inside the LWSBS are reconstructed on constant net stress planes using fifth-order Bezier curves to generate smooth, continuous, and nonintersecting suction surfaces. Application to kaolin and Merri Creek soils produces suction profiles consistent with reported experimental trends, including suction reduction during constant moisture loading and a distinct transition in contour curvature across the LOO. The reconstructed suction surfaces preserve the fundamental structure of the MPK framework while providing the first explicit continuous hydraulic representation of suction within the MPK volumetric state space. They enable estimation of suction at intermediate soil states where direct measurements are unavailable, facilitate comparison with conventional suction-based interpretations, and establish a foundation for future constitutive, numerical, and coupled hydromechanical modelling within the MPK framework.
Abstract Noncompliance with regulatory requirements during residential construction remains a persistent issue in Australia, often leading to costly defects, compromised safety, and reduced building performance. This study identifies the most common compliance risks in low-rise residential buildings and develops two practical tools to support proactive defect mitigation: (1) a regulatory-aligned framework that maps frequent noncompliant building works to relevant provisions of the National Construction Code, Australian Standards, and Australian Building Codes Board Housing Provisions; and (2) a Bayesian beta-regression forecasting model for predicting future noncompliance rates. Using 15 quarters (2020–2024) of compliance data from the Victorian Building and Plumbing Commission and 3,743 private inspection records, a thematic analysis was conducted, which revealed that timber framing, footings and slab construction, weatherproofing of brickwork, and waterproofing works exhibit the highest rates of noncompliance. The proposed framework demonstrates clear linkages between recurring compliance risks and their underlying regulatory obligations, providing a practical reference for builders and supervisors. The Bayesian beta-regression model, validated through posterior diagnostics and out-of-sample testing, showed strong predictive capability for forecasting timber-framing noncompliance, with the results indicating a gradual upward trend across future quarters. Collectively, the regulatory-aligned framework and the predictive model offer construction practitioners and regulators structured, evidence-based tools to enhance compliance oversight, improve training, and reduce rework, thereby supporting safer and higher-quality residential construction.
Large language model (LLM) watermarking is a prominent approach for identifying machine-generated text, supporting provenance, protecting intellectual property, and enabling accountability in generative-AI ecosystems. Proposed mechanisms include token- and logit-based sampling, semantic and syntactic watermarking, post-hoc methods, publicly verifiable schemes, model- and service-level watermarking, and retrieval-augmented or application-specific approaches. However, their practical reliability under realistic transformations, adaptive attacks, limited model access, diverse deployment environments, and high-stakes governance settings remains uncertain. This article presents an evidence-centered, PRISMA-guided systematic literature review based on searches completed on 14 May 2026. Rather than only classifying mechanisms, we assess how convincingly existing studies support their reliability and robustness claims. We identified 1367 records, retained 1065 after duplicate removal, assessed 207 full texts, and included 172 studies. The synthesis covers six themes: watermark embedding paradigms; threat models and attacker assumptions; evaluation metrics and experimental design; robustness under post-generation transformations; deployment readiness and access assumptions; and the limited evidence on application, governance, and misuse contexts. The field is methodologically rich but evidentially fragmented: many studies report strong detection performance while relying on narrow datasets, inconsistent metrics, limited baselines, implicit threat models, unrealistic transformations, or access assumptions unsuitable for closed or API-based deployments. Recurring concerns include false-positive control, public verification, adaptive paraphrasing, mixed-origin documents, benchmark fragmentation, and reproducibility. We therefore provide a descriptive evidence-completeness assessment and a research agenda for more robust, transparent, and deployment-ready LLM watermarking systems.
