Blockchain Papers

K Takahashi

This preprint develops a contract-based framework for evaluating operational claims in open, partially observable, and potentially adaptive systems. Rather than treating safety, service delivery, resilience, or recovery as intrinsic attributes of a system, it represents them as typed, evidence-carrying propositions relative to a declared physical and institutional boundary, environment mechanism, observation history, intervention regime, policy class, shared resources, and finite physical horizon. The framework integrates hybrid path-space models generated by a common modular mechanism; exact physical ledgers that distinguish atomic events from non-atomic finite-variation flows; calibrated observation models and measurement uncertainty; causal identification and transportability; scenario-fixed experiment interfaces; and policy-uniform correspondences between evidence models, computable concrete models, and abstractions. Its principal formal result is a finite-horizon, one-sided deployment certificate that transfers an abstract lower safety value to deployment under partial observation. Statistical coverage over learning datasets, deployment-path probabilities, reconciliation discrepancies, and implementation or abstraction radii are kept as distinct quantities rather than combined into a single confidence score. Claim-sufficient scopes are not assumed to be unique. They are evaluated through a Pareto profile covering completion nonemptiness, query diameter, decision stability, action support, latent sensitivity, and query type. Explicit verdict semantics distinguish accepted claims, contradictions, unsupported refusals, unresolved decision margins, incomparable claims, and invalid records. A machine-readable implementation based on JSON Schema Draft 2020-12 and exact decimal arithmetic checks finite types, relation coverage, physical balance, provenance exclusivity, artifact containment, hashes, and recomputation of certificate quantities. Synthetic examples involving a distributed AI service and human–AI emergency logistics, together with finite counterexamples and reproducible stochastic fixtures, illustrate the framework. The validator does not establish the truth of external evidence, causal assumptions, statistical models, or real-world safety. The work does not propose a universal performance scale, a new causal calculus, or a replacement for formal assurance cases or runtime monitoring.

Gabriela Mariutac, Claudiu Brândaș, Otniel Didraga, Mihai Plesa

The voluntary carbon market (VCM) has faced sustained legitimacy stress since 2023, when peer-reviewed work found that fewer than one in six issued credits represented a real emission reduction. In parallel, tokenisation through Web3 protocols, decentralised autonomous organisations (DAOs), and regenerative finance (ReFi) infrastructures introduced new participants interacting with incumbent registries without a shared coordination framework. Existing scholarship examines commons governance, complex system governance (CSG), and tokenised carbon markets largely in isolation; the gap addressed here is the absence of an integrated system-of-systems (SoS) governance treatment of the tokenised VCM. This study develops and empirically applies a polycentric SoS governance framework for the tokenised VCM, structured around four research questions and five foundational contributions. We treat the tokenised VCM as an SoS that is polycentric in configuration but not by design, and develop a system-of-systems engineering (SoSE) governance reading of it. We reformulate Ostrom’s eight design principles as SoS governance criteria for digital–physical hybrid commons, map each to CSG metasystem functions, and apply the framework to four cases: KlimaDAO, Toucan Protocol, Regen Network, and the post-2023 Verra reforms. Qualitative coding is complemented by on-chain and Base Carbon Tonne spot-price evidence from October 2021 to December 2025. Disclosure by an analytical intermediary acted on the SoS roughly seven weeks before formal regulatory action and was associated with about 90% of the observed bridging slowdown, interpreted descriptively rather than causally. We derive an eight-item reform agenda, six DAO–registry interface specifications, and a five-level governance maturity rubric.

Samuel Glasscock

My technical project is a web-based system design simulator app. Specifically, this project is an educational tool used to bridge the gap between industry expectation and the preparation of entry level software engineers. Through a turn-based simulation, users engage in experiential learning, showing how each decision made influences the immediate steps and system state, as well as how those decisions cascade in the more long-term project context. Each decision triggers a new event, allowing users to choose an option to address a given event. There is no clear “correct” option but instead emphasizes tradeoffs and how those tradeoffs affect system architecture. The system architecture is exposed through two means. First, a metrics panel is presented to a user, with metrics like reliability, architecture complexity, performance, latency, and real-world constraints like budget. Secondly, a software architecture diagram is presented to the user as a main focus of the screen, allowing the user to refer to it for a visual representation of the internal system state as a level of abstraction expected in system design scenarios. Specifically, the software diagram has nodes and edges between the high-level components to represent major parts of a system. Both the metrics panel and software diagram update per decision, showcasing the current system state and highlighting the effect a decision had through. In particular, a slider representing the metrics tracked adjusts (via animation) and also provides color-themed feedback on the state of those metrics (“good”, “warning”, “critical”). Depending on the event, the system highlights relevant nodes and edges to indicate to the user where in the system the newest issue is, allowing users to focus on the problem area, but also maintain a perspective of the system at large, as to not lose focus of more long-term goals. The project includes multiple “worlds”, which simulate a junior software engineer being assigned to a new project, and each world has its own events and action options to take. After playing a session, users can review their decisions to further inform their future decisions. My STS project explores the paths that governance power is redirected through in Decentralized Autonomous Organizations (DAOs). By juxtaposing the DAO imaginary with the realities limited by their implementation in practice, I expose the true outcome of their network. Specifically, I examine how proposed DAO theoretical attributes reveal themselves through a case study of CityDAO. While exploring the lifetime of CityDAO, I apply Actor Network Theory (ANT) to model CityDAO in particular (and DAO processes more broadly) as a network of human and non-human actors. In this network, each actor delegates a level of agency to each other actor it interacts with. I highlight how agency is assigned from each actor to others, and how each actor reshapes the ultimate outcome of the system. However, not all actors are equal. Rather, some actors function as obligatory passage points, through which all proposals must flow and cannot proceed unless this actor allows the proposal to proceed. Through my analysis, I identify membership NFTs, informal member forums, DAO members, DAO leaders, and formal vote signaling tools as actors in this actor network. I also identify multi-signature wallets, registered legal agents, and DAO-oriented legislation as obligatory passage points. By examining this network, I reveal the controlling role that multi-signature wallets, registered legal agents, and supporting DAO legislation plays in the proposal process. These obligatory passage points hold ultimate governance power, since if any of them fail or reject a proposal, the entire system process up until that point’s intentions are unrealized. While not highly correlated in a direct way, these two projects complement each other by emphasizing system/network level perspectives of visualizing sociotechnical systems and processes. My technical project focuses on users building their understanding of system architecture, while my STS paper reveals the critical points where power lies in the DAO proposal process. Together, the system-building skills learned from the technical project may be applied alongside the strengths and limitations revealed through the network in the STS project to enable us to design systems that more adequately allocate power among all actors moving forward.

Aditya Rautaray

Modern systems face limitations imposed by centralized control. These limits lead to single points of failure, uneven information flow, and slow decisions. I present a multi-layer mathematical model for human-centric, decentralized systems. Our model offers quantitative tools to identify and reduce bottlenecks by distributing decisionmaking. The framework introduces core metrics: Bottleneck Index, Decentralization Degree, Decision Efficiency Function, Collective Intelligence Score, and Resilience Index. A four-layer architecture—Strategic Human Decision, Decentralized Coordination, Autonomous Agent, and Technical Infrastructure—is described. We validate the approach using thematic analysis and simulation across organizational, healthcare, and autonomous settings. Ablation studies show that modular design, self-organization, and adaptability reduce bottlenecks. The system improves CIS by 41.3% over centralized systems. This framework guides engineers and leaders to build resilient sociotechnical systems

Theodore K. McClendon

This paper identifies a pervasive yet under-recognized failure mode in modern computation, engineering, and education: the "wrong mindset" of early collapse of superposition. Complex problems are routinely fragmented into isolated domains, subjected to fast parallel formal modeling, and forced into premature consensus predictions before integrated synthesis can occur. The result is systemic decoherence-the loss of coherent understanding precisely when stakes are highest. Examples include the Avcoat heat-shield permeability issues observed on Artemis I (caused by insufficient material permeability leading to gas entrapment, pressure buildup, cracking, and char loss under skip-entry conditions), which persisted as a managed risk into Artemis II despite extensive domain-specific modeling and investigation. Similar patterns appear in organizational design, such as Strategy (formerly MicroStrategy) operating a sovereign-scale Bitcoin treasury alongside legacy centralized business intelligence systems without a unifying coherence layer. In education, speed-driven rituals like the early-grade "race to the board" condition young minds to prioritize rapid convergence over relational insight, dissolving innate coherence capacities. Compounding the issue is the massive processing-speed imbalance between human minds and machines. Education must explicitly teach this reality-not as alarm, but as a call for wise labor distribution: humans as the sovereign coherence substrate (bringing relational insight, empathy, and mortality awareness), machines as instruments of speed and scale. The proposed corrective geometry, Triangulus SBV-0, inverts the default mindset. Core Alpha and Core Beta sustain explicit superposition; Core Gamma (the Synthesizing Generalist) serves as the primary human coherence node during TT Think Time; collapse occurs only through intentional, staked, lived-experience-weighted synthesis attested by the Proof of Accuracy protocol. This demands a fundamental re-imagining and restructuring of education and professional practice. Substantial paradigm friction is anticipated, including skepticism tied to the author's lack of traditional advanced credentials. Such resistance is addressed directly as symptomatic of the diagnosed mindset. Coherence is not an optional feature-it is the foundational substrate. Triangulus SBV-0 offers a civilizational inversion capable of producing more resilient, humane outcomes when rigorously tested.

Kolja Sahm, George M. Giaglis

The nomenclature of Decentralized Autonomous Organizations (DAOs) implies a capability for autonomous operation that remains theoretically undefined and empirically unverified. This paper addresses this blind spot by reframing DAO analysis through a reductionist systems engineering lens, defining autonomy strictly as a system’s capacity to achieve goals under uncertainty without external intervention. We propose a novel measurement framework adapted from robotics standards (0–5 scale) and apply it to a random sample of N= 50 DAOs. The results reveal a stark disconnect between promise and reality: the ecosystem is currently capped at agency (Level 3), with the vast majority functioning merely as automated, human-dependent systems. Through an ordered logit analysis, we demonstrate that while architectural design choices, specifically regarding governance formalization and oracle integration, drive lower-level automation, the probabilistic reasoning required for high autonomy is statistically absent. We conclude that until the technical barriers to artificial intelligence integration are overcome, the ecosystem will remain “DAOs in Name Only,” failing to fulfill the autonomous promise of their title.

Kent Douglas Lambert, Tom Bradley, John M. Borky, Steve Simske · 6 authors

This research identifies a set of practical solutions to the uncontrolled growth of malicious cross-industry cybersecurity threats. Given the presence of the behaviors and negative effects of cyber threats, the research seeks to understand the effects of three eco-system-wide strategies for cyber defense: Defense-in-Depth (DiD), Zero-Trust Architectures (ZTA), and secure cryptographic key provisioning. These strategies are developed using the BlockFrame, Inc., Eco-Secure Provisioning™ (ESP™) Framework, blockchain-assisted digital logistics management and governance, and the application of Emergence Theory and Uniformity. The research addresses five specific questions to organize the approach, with practical translations of this research to selected industrial use cases.

Hasan Heydari, Alysson Bessani, Kartik Nayak

Existing distributed ledger protocols either incur a high communication complexity and are thus suited to systems with a small number of processes (e.g., PBFT), or rely on committee-sampling-based approaches that only work for a very large number of processes (e.g., Algorand). Neither of these lines of work is well-suited for moderate-scale distributed ledgers ranging from a few hundred to a thousand processes, which are common in production (e.g, Redbelly, Sui). The goal of this work is to design a distributed ledger with sub-linear communication complexity per process, sub-quadratic total communication complexity, and low latency for finalizing a block into the ledger, such that it can be used for moderate-scale systems. We propose QScale, a protocol in which every process incurs only $\widetilde{O}(κ\sqrt{n})$ communication complexity per-block in expectation, $\widetilde{O}(nκ)$ total communication complexity per-block in expectation, and a best-case latency of $O(κ)$ rounds while ensuring safety and liveness with overwhelming probability, with $κ$ being a small security parameter.

Jinzhi Lu, Xiaochen Zheng, Zhenchao Hu, Huisheng Zhang · 5 authors

Model-based Systems Engineering (MBSE) has been widely utilized to formalize system artifacts and facilitate their development throughout the entire lifecycle. During complex system development, MBSE models need to be frequently exchanged across stakeholders. Concerns about data security and tampering using traditional data exchange approaches obstruct the construction of a reliable marketplace for digital assets. The emerging Distributed Ledger Technology (DLT), represented by blockchain, provides a novel solution for this purpose owing to its unique advantages such as tamper-resistant and decentralization. In this paper, we integrate MBSE approaches with DLT aiming to create a decentralized marketplace to facilitate the exchange of digital engineering assets (DEAs). We first define DEAs from perspectives of digital engineering objects, development processes and system architectures. Based on this definition, the Graph-Object-Property-Point-Role-Relationship (GOPPRR) approach is used to formalize the DEAs. Then we propose a framework of a decentralized DEAs marketplace and specify the requirements, based on which we select a Directed Acyclic Graph (DAG) structured DLT solution. As a proof-of-concept, a prototype of the proposed DEAs marketplace is developed and a case study is conducted to verify its feasibility. The experiment results demonstrate that the proposed marketplace facilitates free DEAs exchange with a high level of security, efficiency and decentralization.

Damien Trentesaux, Raphaël Rault

Autonomous non-military cyber-physical systems are widely studied in research but there are still few applications in industry. One of the reasons relies in the fact that there is still no proof of guarantee for these systems regarding their safety and their ability to behave in a nonhazardous way, mainly because of the induced complexity caused by their learning abilities coupled with the high ability to interact and cooperate of their composing mechatronics elements. More, cyber-physical systems are intended to be merged into socio-technical systems and interact with humans. As a consequence, the study of their ethical behavior translates currently a major stake. Meanwhile, it is clear that this stake is still not address by the scientific community while 1) sci-fi literature and movies have addressed this since a long time 2) some autonomous road vehicles have already injured people, and 3) EU parliament has launched a procedure dealing with the establishment of civil laws for autonomous learning robots. This paper intends then to open the debate on this topic and suggests to extend dependability studies to integrate ethicality as a new dimension. New emerging research fields are identified and an illustration in the autonomous train transportation is presented.

Dominik T. Heber, Marco W. Groll

Complexity of electric/electronics (E/E) in automobiles increases tremendously due to more connectivity and real-time data processing. Hence, huge volatility of E/E artifacts is the consequence. In order to keep track of all changes made from early systems engineering to late after sales, a permeable traceability in data management systems has to be achieved. Therefore, this elaboration adapts the blockchain technology to achieve traceability of E/E development artifacts from early model-based systems engineering (MBSE) till after sales. By this, MBSE is linked to product data management and the automobile’s configuration is known at each instant of time. The Digital Twin, a digital, domain-specific representation of the physical vehicle in one front end tool, makes the complexity still feasible to handle and is empowered by the blockchain. Hence, traceability of E/E artifacts over an automobile’s lifecycle including MBSE is fostered in a manageable manner.