AI-assisted cybersecurity systems are characterised by continuous adaptation between attackers and defenders, making evolutionary game theory a natural framework for studying their long-term behaviour. However, existing evolutionary cybersecurity models have primarily focused on homogeneous interactions, providing limited understanding of how population structure influences cyber attack–defence dynamics. In this paper, we develop a mixed-role evolutionary game in which adaptive cyber agents can exhibit both offensive and defensive behaviours, and investigate its dynamics in well-mixed and structured populations. The proposed framework combines stochastic evolutionary analysis with large-scale agent-based simulations to examine how interaction structure shapes long-run strategic behaviour. Our results reveal a fundamental difference between global and local interactions. While well-mixed populations exhibit broad coexistence between attacking and defensive strategies, structured populations generate well-defined evolutionary regimes in which secure defensive behaviour becomes dominant over a much larger region of the parameter space. Spatial analysis further shows that neighbouring defenders naturally form resilient clusters that suppress persistent attacks through network reciprocity. These findings demonstrate that interaction structure is a fundamental determinant of AI-assisted cybersecurity evolution and suggest that organising defensive agents through local networked interactions can substantially improve long-term cyber resilience without requiring additional defensive incentives.
The early-stage detection of alpha-synuclein (alpha-Syn), a hallmark biomarker of Parkinson's disease, is critical for timely diagnosis and therapeutic intervention. Herein, we report on a metal-enhanced fluorescence (MEF) immuno-biosensor constructed from a nanohybrid comprising glutathione (GSH)-capped CdSe/In2S3Se quantum dots (QDs), multishaped AuCu alloy nanoparticles (NPs) and reduced graphene oxide (rGO). The QDs-AuCu alloy NP-rGO nanohybrid was prepared via solution-phase assembly and anti-alpha-Syn antibodies (Ab) were immobilized via physical adsorption. Target alpha-syn interaction triggered fluorescence amplification, which was further supported by finite difference time domain (FDTD) simulations revealing localized electric field enhancement at the QDs-AuCu alloy NP-rGO interface. Notably, the QDs-AuCu alloy NP-rGO nanohybrid exhibited enhanced redox currents and reduced impedance, reflecting a synergistic contribution from the QDs, plasmon-active AuCu NPs and conductive rGO scaffold in facilitating efficient charge transport and interfacial electron transfer. Density functional theory (DFT) calculations revealed that introducing an In2S3Se shell around GSH-CdSe QDs led to a significant reduction in the HOMO-LUMO energy gap from 0.323 eV to 0.013 eV which was accompanied by a downward shift in the Fermi level from-1.99 eV to-4.10 eV. Post-self-consistent field (SCF) analysis of electron density and electrostatic potential (ESP) maps confirmed increased electron delocalization and a stronger internal dipole moment in CdSe/In2S3Se QDs compared to CdSe, as evidenced by compact density contours and intensified polarity in the ESP profiles. These changes were driven by increased orbital delocalization and stronger interfacial electronic coupling between core and shell atoms, thus confirming the role of the core/shell architecture in enhancing charge transfer and electronic conductivity. The QDs-AuCu alloy NP-rGO-Ab immunosensor achieved a wide dynamic detection range from 0.01 to 100 pg/mL, a limit of detection of 5.6 fg/mL and high recovery rates (94.0-99.4%) in spiked human serum. In addition, cytotoxicity assessment using HEK293T cells demonstrated that the QDs and QDs-AuCu alloy NP-rGO nanohybrid retained high cell viability across all tested concentrations whilst stability studies conducted in acidic buffers (pH 1 to pH 5) and in biologically relevant media, showed that the QDs remained structurally stable with no observable degradation or loss of optical performance.
Nudiviruses are double stranded DNA viruses known to infect arthropod hosts. Around 20 different nudiviruses have been identified from crustacean hosts alone. In crustaceans, the hepatopancreas is the primary target of infection, where nuclei appear hypertrophic under histological preparation due to a growing intranuclear viroplasm. The Jonah crab, Cancer borealis, is the target species of an emerging fishery located in the New England (USA) region. Histological and metagenomic tools were used to characterize a new nudivirus, including pathological characterization and sequencing of the 97,677 bp genome, which encoded 93 open reading frames. The genome housed a genetic synteny that was similar to other gammanudiviruses. The virus also phylogenetically clusters with other members of the Gammanudivirus genus based on a 17-protein concatenated phylogenetic tree. Comparative genomics revealed up to 66 conserved genes across all Gammanudivirus species, including a putative deneddylase that appears not to be present in all other nudivirus lineages. Discovering and identifying this nudivirus provides greater detail on a new pathogen that poses a potential risk to the emerging fishery.
This study focused on the development of insulating refractory bricks using quartzite, with a comprehensive analysis of their mechanical and thermal properties. The bricks were made from quartzite with 10% bentonite binder and water, added for mixing. Various tests were done (Xray Fluorescence, Thermogravimetric and Differential Thermal Analyses, apparent porosity, shrinkage, Loss on Ignition (LOI), compressive yield stress, and water absorption (WA)), following American Society for Testing and Materials' procedures. Microstructural analysis of the sample was observed using Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (SEM-EDS). These results provided valuable insights into the stability of the developed refractory bricks at high temperatures. Analysis of chemical composition from quartz bricks revealed significant SiO2 content (94.303%), emphasizing the material's superior refractory properties. LOI (0.5%) and shrinkage (0.2%) results indicated enhanced performance with good thermal stability and strength. Compressive stress yield indicated that the material exhibits good strength relative to the amount of binder used. WA results confirmed that the brick sample is suitable for high-temperature applications. SEM/EDS analysis unveiled intricate microstructural features, affirming the bonding agent's influence on the material's composition.
Institutional incentives are widely used to promote cooperation among autonomous, self-regarding agents, from human societies to multi-agent and AI systems. Existing work typically treats incentive design as a bi-objective problem: minimise institutional cost while achieving a high long-run frequency of cooperation. Whether such schemes also maximise social welfare-total population payoff net of institutional expenditure-has remained largely unexplored. We develop a welfare-centric framework for institutional incentives in finite, well-mixed populations playing a social dilemma (Donation Game and Public Goods Game), considering both rewards for cooperators and punishments for defectors. For each mechanism, we derive explicit expressions for expected social welfare and characterise how it depends on incentive efficiency and selection intensity. Analytically, we identify parameter regimes where social welfare has a single optimal incentive level and regimes with qualitative phase transitions, in which welfare becomes non-monotonic with multiple local optima. We prove that any welfare-maximising incentive is either zero or concentrated around a simple closed-form target, and we provide an efficient algorithm to compute these optima. Comparing rewards and punishment, we further derive closed-form conditions under which rewards outperform punishment in terms of social welfare for any given budget. Overall, our results reveal a systematic gap between incentives optimised for cost or cooperation frequency and those that maximise welfare.
