Public research outputs.
Public research outputs document the evolution of APS Logic from phase-state analysis and Silent Convergence Window™ toward a domain-agnostic analytical framework for producing a quantitative reading of dynamic system state and resilience change.
APS Logic Foundations
Foundational publication defining APS Logic as a phase-state analytical approach to reading how system conditions change before visible instability.
Silent Convergence Window
Publication focused on the phase in which a system may appear stable while losing recovery capacity and entering a vulnerability window.
From Events to Conditions
Cyber-domain publication presenting APS Logic as a systemic framework for reading pre-event and pre-attack changes in system condition.
Cyber and post-quantum research outputs.
Additional public Zenodo records extend the APS Logic evidence track toward cyber fragility, national and European early warning models, post-quantum transition risk and cryptographic inventory assessment.
Cyber Fragility Index (CFI): A Composite Indicator for Predictive Cybersecurity Governance
Public research output introducing a composite indicator for predictive cybersecurity governance and cyber fragility assessment.
National and European Cyber Fragility Index (NCFI / ECFI): From National Predictive Surveillance to a European Early Warning System
Public research output extending the cyber fragility concept from organizational assessment toward national and European early warning perspectives.
Measuring Organizational Fragility in the Post-Quantum Transition: The Post Quantum Fragility Index (PQFI)
Public research output focused on organizational fragility during the transition toward post-quantum cryptographic readiness.
Crypto Inventory Framework for Automated Post-Quantum Fragility Assessment
Public research output addressing cryptographic inventory as a foundation for automated post-quantum fragility assessment.
Historical field and corporate applications.
The path that led to APS Logic includes a long history of real-world predictive prevention, territorial decision support and corporate loss-prevention applications. These results belong to the historical lineage of APS Logic and are kept distinct from current deployments and later controlled validation campaigns.
Predictive prevention tested in operational urban environments
XLAW transformed the earlier territorial research line into an operational predictive-preventive framework for patrol prioritization and earlier deployment of available resources.
Reported historical field results:
11 Italian Police Headquarters involved in the historical deployment path;
−24% predatory crimes;
+54% arrests in flagrante delicto;
approximately 3 hours predictive lead time.
The historical validation path included institutional evaluation within the Italian public-security environment and academic / research review. These figures describe the documented XLAW historical perimeter and are not automatically transferred to APS Logic or APS-SU performance claims.
Loss prevention, security allocation and economic impact
Historical Retail and GDO applications applied anticipatory system-state interpretation to store exposure, inventory-related risk, operational pressure and the allocation of security resources.
Historical corporate evidence reported material changes in inventory differences, security allocation and security-management costs. Economic impact and ROI therefore belong to the results of these Retail / GDO applications rather than constituting a separate application.
From XLAW and field evidence to APS Logic
Across urban security and corporate applications, the recurring analytical question was the same: can a changing condition be recognized early enough to improve the decision before the visible outcome dominates?
APS Logic formalizes this long operational trajectory into a domain-agnostic analytical framework. Historical XLAW maturity and historical Retail / GDO results remain evidence of lineage; they are not used as automatic performance claims for the current APS Logic runtime.
Current operational applications.
Current operational status is kept separate from historical field evidence and from experimental or validation-only applications.
Current operational urban-security reference
APS-SU is the urban-security verticalization of APS Logic, publicly presented as PELTA Sicurezza Urbana. It applies system-state reading to changing territorial conditions, operational continuity and resource prioritization.
The public evidence base includes historical field continuity, a demonstrated operational reference and a partner-delivery line. Other APS domains are represented below according to their actual experimental or validation maturity.
Validation and cross-domain evidence.
APS Logic has been evaluated through controlled validation, causal replay, blind holdout, historical blind replay, forward validation and external technical evaluation. Protocols differ by domain; the analytical framework remains common.
APS-CYBER validation path
Controlled real-data validation examined measurable changes in cyber-system state before later instability within declared observation windows.
External Technical POC Completed. APS-CYBER subsequently completed an external U.S. cybersecurity technical Proof of Concept using real enterprise Microsoft 365 security data. The formally closed evaluation found the predictive-analysis approach credible, consistent and genuinely different, with real potential as the technology progresses toward full product maturity.
External technical evaluation · real enterprise data · no certification implied.
APS-BIO-LAB
Atrial Fibrillation experimental case. Controlled analysis identified a restricted high-specificity dynamic phenotype compatible with a strong Silent Convergence Window in a subset of pre-event trajectories.
HILO / Aktiia · Historical Blind Replay. A second biological evidence path extended the framework to real blood-pressure time series across 1,131 real measurements.
Experimental physiological-signal evidence only. No clinical prediction or diagnostic use is established.
Three complementary validation paths
NASA IMS Bearing. Causal run-to-failure replay across 982 observations recorded a Silent Convergence Window before the withheld terminal reference, with 46h 30m lead in the declared sequence.
NASA C-MAPSS FD001. Blind holdout validation across 20 units produced 1.00 precision on the SCW subset and 4.0x enrichment of the high-risk population within the declared perimeter.
Infrastructure System. Controlled historical replay used seven pre-event observations from the same subsystem across a 2003–2018 longitudinal sequence.
Protocol-specific experimental evidence. No universal industrial performance guarantee is implied.
Causal replay + forward validation
External financial series. Four external fund series plus MSCI World: 29,537 evaluations, 3,659 resolved directional episodes, 77.29% directional accuracy.
Five U.S. stocks · forward validation completed. AAPL, ABNB, ADBE, AFRM and AI: 1,904 resolved directional episodes and 88.71% directional accuracy.
AAPL dedicated forward observation. 374 resolved directional episodes and 89.30% directional accuracy.
Core modified: NO · instrument-specific tuning: NO. These are validation results, not portfolio returns, trading performance or investment advice.
First Level 4 internal controlled assessment completed.
APS-CYBER completed the first internal controlled assessment under APS Logic Standard at Level 4 — Predictive Resilience. All 10 applicable requirements out of 10 were satisfied within the declared assessment perimeter.
Evidence integrity was SHA-256 verified. The result is an internal proprietary assessment; independent review is pending and no accreditation or accredited certification is claimed.
Cross-domain evidence does not imply domain equivalence. Results are interpreted only within the declared dataset, protocol and validation perimeter of each campaign.
Evidence policy
Detailed numbers, public claims and third-party references are published only when supported by public documents, official sources, publications or controlled validation reports. Quantitative metrics validate results only within their declared scenario, dataset or technical perimeter, observation window and validation method; they are not universal performance guarantees.
APS Logic does not publish protected formulas, weights, thresholds, guard rules, transition internals, memory logic, rule traces or reserved scoring internals.