Website: https://manual.warondisease.org/knowledge/proof/wishonias-wager.html Abstract: There's a non-zero possibility that hell exists, and that you and everyone you love is going to die and burn in it for eternity. As it is very hot in hell, this would be unfortunate. There's also a non-zero possibility that biotechnology lets you feel very good for an indefinitely long period of time. Expected value is the chance of a thing multiplied by the size of it, and if you multiply infinity by any likelihood at all, even 0.0000001%, it's still infinity. So the expected value of doing nothing is infinity bad, and the expected value of acting is infinitely good, even if there's an extremely low probability that any of this is true. The cost of acting is finite: roughly one share of a company that makes missiles. This paper argues that when one outcome is infinitely terrible and the other is infinitely good, any finite action that shifts the odds from the first toward the second is rational, and that the cheapest such action available is redirecting the resources your governments waste being really good at killing the taxpayers who pay for them. (They currently spend 604 (95% CI: 453-894) times more on the military than on the clinical trials that would cure the diseases doing the killing.) It's Pascal's wager with the broken parts replaced: one hypothesis instead of a thousand gods, real evidence instead of none, an action that actually changes the outcome, and a stake of one share instead of your eternal soul. Summary: A reconstruction of Pascal's Wager with its defects removed. Two propositions cannot be disproven: that a conscious being may suffer without end, and that it may flourish without end. Both carry nonzero probability and infinite magnitude, so any finite action that shifts probability from the first toward the second has unbounded expected value. Unlike Pascal's, the wagered action is empirical, not theological: funding the clinical trials that extend healthy lifespan and modify conscious experience.
Open access
2 source records
Neuroethics, Human Enhancement, Biomedical Innovations
Peer-to-peer (P2P) energy trading requires network-aware coordination because transactions are physically realized through distribution networks. However, sensitivity-based coordination causes a confidentiality-verifiability tradeoff, as network sensitivities may reveal vulnerable components while undisclosed sensitivities prevent participants from verifying utility-provided transaction guides. This paper proposes a zero-knowledge-proof-based method for verifying the computational integrity of network-constrained transaction guides with respect to committed private network data, without exposing network-sensitivity information. The guide defines admissible injection and withdrawal volumes derived from sign-decomposed sensitivity matrices while satisfying balance, voltage, line-flow, and optimality conditions. These conditions are encoded in an arithmetic circuit, represented as R1CS constraints and a quadratic arithmetic program, and verified using a bilinear pairing. Blockchain commitments bind the approved circuit, public inputs, statement identifiers, proof, and verification result for tamper-evident auditability. The proposed proof certifies correct guide computation from committed network data; the authenticity of the committed network data is handled through an explicit registration and attestation assumption. Case studies on a modified IEEE 33-bus system show satisfaction of network constraints after clearing, rejection of public-input and witness-inconsistency attacks, and practical on-chain overhead, with an 806-byte proof.
Bilateral attribute-based access control for data trading must hide policies, provide cryptographic fairness, and avoid trusted third parties. Existing solutions either leak policy information, incur super-linear costs, or rely on trusted dispute resolution. We present PriME-Deal, a non-interactive protocol that simultaneously achieves policy-hiding bilateral matching, efficient threshold access control, and auditable fair exchange on public blockchains. The seller embeds a secret token under the buyer policy into an oblivious key-value store with pseudorandom masking; the buyer reconstructs the token locally via tag-based probing, eliminating combinatorial enumeration, and proves correctness in zero-knowledge. Fair exchange is enforced through a collateralized on-chain reveal with a cryptographic audit that penalizes misbehaviour without trusted parties. We prove security in the Universal Composability framework under standard assumptions. Compared with the state-of-the-art threshold fuzzy IB-ME scheme, the seller's publishing time is reduced by two orders of magnitude (e.g., 8.76s vs. 690s for a policy of 500 attributes). For a typical configuration of (200,20,5), the buyer completes token reconstruction and proof generation in 8.9s, with the zero-knowledge proof taking under 0.6s and remaining constant across all parameter scales. The on-chain cost is approximately 28.6M gas, well within Ethereum's block limit. PriME-Deal thus delivers the first practical privacy-preserving data trading protocol that combines linear seller overhead, bilateral policy hiding, and auditable fairness.
Abstract The increasing use of residential distributed energy resources (DERs), including photovoltaic generation, electric vehicles, stationary batteries, and flexible electric water heaters, is changing the operation of low-voltage distribution networks. These resources can reduce household electricity costs and provide demand-side flexibility; however, uncoordinated operation can result in voltage deviations, network congestion, line overloading, and stress on distribution transformers. This paper presents a code-grounded comparison of three DER coordination architectures: decentralized household-level optimization, centralized feeder-level optimal power flow (OPF), and hierarchical aggregator-based coordination. The benchmark is conducted on a three-phase low-voltage distribution network with 157 residential households over a 24-hour horizon. The decentralized architecture optimizes each household individually, and the resulting network behavior is validated in OpenDSS. In the centralized architecture, detailed household DER models are integrated into a nonlinear AC-OPF formulation. The hierarchical architecture coordinates prosumer flexibility using local flexibility estimation, network-level activation, allocation, household-level tracking, and final OpenDSS validation. For the studied feeder, the results indicate that the hierarchical architecture provides the most favorable physically validated trade-off between customer economics and network performance among the three architectures considered. Compared with decentralized control, it decreases the mean daily household electricity cost from 6.74 to 6.14 GBP/home/day (an 8.9% reduction), reduces network peak demand by 20.4%, reduces the worst line-loading ratio by 15.3%, and reduces transformer loading by 19.0%. In this case study, all 157 households obtain lower daily electricity bills than under the decentralized baseline, indicating that the incentive-based coordination mechanism can align network-level objectives with individual customer benefits under the modeled conditions. The centralized OPF achieves the strongest nominal network performance but relies on restrictive assumptions regarding full DER observability and controllability and does not provide the same customer-level autonomy, compensation, or implementation pathway as the hierarchical framework; it is therefore treated as an idealized network benchmark rather than a directly deployable controller. It should be noted that the hierarchical architecture reduces, but does not fully eliminate, network constraint violations and that these findings are obtained for a single feeder under deterministic daily input profiles. Overall, the results suggest that DER coordination strategies should be assessed using a holistic framework that considers customer cost, network security, flexibility realization, fairness, computational effort, and physical validation, and that, under this broader evaluation, hierarchical coordination offers a practical compromise between decentralized autonomy and centralized optimality for the studied network.
India's Unified Payments Interface (UPI) processes billions of transactions monthly across dozens of Payment Service Providers (PSPs). However, a structural architectural gap persists: no single entity maintains a unified, real-time, immutable view of an individual's complete financial transaction graph across competing platforms. This fragmentation has become the primary mechanism enabling complex UPI digital payment fraud and mule-account networks. Scammers easily spin up identities across multiple platforms, quickly cascade stolen funds across PSP boundaries, and discard the handles, leaving a broken trail that takes weeks for law enforcement to piece together. This white paper proposes the Universal Financial Identity (UFI) system—a sovereign, mobile-number-anchored financial identity layer that federates all of a user's UPI handles, bank accounts, and Central Bank Digital Currency (CBDC/e-Rupee) wallets into a single, immutable distributed ledger record. Key Architectural Features: Zero-Action Trigger Mechanism: The permanent UFI record (formatted as <mobilenumber>@ufi) is generated automatically in the background at the exact moment a user links any bank account to a UPI application, requiring zero user friction. Immutable Distributed Ledger Layer: Operates as a permissioned Hyperledger Fabric network managed by sovereign nodes (RBI, NPCI, and authorized banks), rendering transaction trails cryptographically non-erasable and resilient against app-side account deletions. Graph Intelligence Layer: Integrates native Neo4j graph analytics for real-time, cross-PSP fraud ring detection, rapid fund-movement velocity tracking, and automated fan-in pattern profiling. Programmable Money Integration: Leverages India's e-Rupee infrastructure to enable purpose-bound, geography-restricted, and expiry-enforced smart contract payments for public welfare disbursements (DBT) and B2B settlements. DPDP Act 2023 Compliance: Built with privacy-by-design principles, using salted SHA-256 identity tokenization and multi-tiered, consent-gated access frameworks via the Account Aggregator network. This protocol layer sits seamlessly below existing Third-Party Application Providers (TPAPs) and above core settlement switches, offering real-time cross-PSP fraud tracing and post-deletion identity recovery without introducing latency into synchronous payment pathways. This paper is released for open public community review, protocol exploration, and technical feedback prior to formal provisional patent filings with the Indian Patent Office (IPO).
Abstract. The accelerating development of Artificial General Intelligence (AGI) raises a fundamental question that Stuart Russell articulated with precision: how do we ensure that increasingly powerful AI systems remain aligned with human values? This paper argues that the answer lies not in constraining AGI, but in building parallel infrastructure that preserves human sovereign will-expression. BeTrueCore Modular System — built on Web3 Intuitive Symmetry Methodology (Web3-ISM) v1.2 — proposes a sociotechnical architecture where AI acts as notary, not judge. Drawing on Gödel's incompleteness theorems, wabi-sabi philosophy, Bayesian evolution, and cryptographic governance primitives (ZK-SNARKs, MACI, Lit Protocol), the system transforms collective human intuition into mathematically verifiable decisions. We argue that BeTrueCore does not compete with AGI — it provides the ethical infrastructure upon which AGI-era governance must be built. Keywords: AGI alignment, gorilla problem, assistive gaming, collective intelligence, digital sovereignty, cryptographic Voting, Weight Unit, voice of silence, self-awareness game, AI as a notary, participatory democracy.
Decentralized Autonomous Organizations (DAOs) enable blockchain-based collective governance, yet existing studies often evaluate DAO governance through isolated mechanisms, particularly voting systems. This narrow view does not sufficiently explain recurring problems such as governance capture, weak accountability, inadequate safeguards, and inefficient resource allocation. This paper proposes a Layered Governance Coverage Model that conceptualizes DAO governance as a system of seven interdependent institutional functions spanning participation, agenda formation, collective choice, safeguards, execution, incentives, and meta-governance. The model uses a four-level strength scale to assess not only whether governance functions are present, but also how strongly they are institutionalized. It is empirically applied to thirty-seven active DAOs through evidence-based coding of publicly available governance artifacts. The results show that governance breadth does not necessarily imply governance maturity: collective choice and execution mechanisms are more developed than accountability, safeguards, and meta-governance. Beyond DAO-native settings, the paper positions governance maturity as a trust and resilience regime for blockchain-based IoT and AI infrastructures, where governance affects security, reliability, data integrity, and risk oversight. The paper discusses AI-enabled governance analytics as a support mechanism for monitoring governance activity, detecting anomalies, and improving governance observability. The proposed framework contributes a structured approach for evaluating and designing resilient governance architectures in DAOs and blockchain-based IoT/AI systems.
The rapid rise of Web3 technologies, representing the third phase of the internet, is creating a decentralized ecosystem that grants users ownership and control. Concurrently, metaverse platforms supported by virtual and augmented reality technologies signify the emergence of persistent, shared digital universes where users interact through digital avatars. These developments necessitate significant changes in consumer rights and protections within digital marketing processes. While decentralized structures and blockchain-based systems enhance user data sovereignty, they also require the development of novel governance and financial frameworks. In this context, existing legal instruments—particularly the European Union’s Digital Services Act, the U.S. Federal Trade Commission guidelines, and the OECD Principles on Digital Economy—are insufficient to address the technological complexities and dynamic evolution of Web3 and metaverse ecosystems. Notable regulatory gaps persist in key areas, including data security, informed user consent, algorithmic transparency, and digital identity governance. Moreover, the marketing of blockchain-based financial instruments such as Decentralized Autonomous Organizations and Non-Fungible Tokens introduces new vectors of consumer risk and legal ambiguity, exacerbating market volatility. The opacity of algorithm-driven marketing and the potential for covert manipulation in AI-powered personalization further erode consumer trust and undermine market integrity. To ensure robust consumer protection in the digital marketing landscape, legal and regulatory frameworks must align with ongoing technological innovation. This includes mandatory implementation of algorithmic explainability standards, establishment of transparent and accountable governance mechanisms for DAOs, and development of enforceable contractual norms and minimum information disclosure requirements in NFT transactions. Furthermore, comprehensive digital literacy initiatives and consumer awareness programs are essential to mitigate emerging risks while optimizing the inclusive potential of Web3 technologies. These policy measures are crucial to safeguarding consumer rights and fostering sustainable trust within the evolving digital marketing ecosystem through 2025 and beyond.
Understanding and predicting how social beliefs evolve in response to events -- from policy changes to scientific breakthroughs -- remains a fundamental challenge in social science. Given LLMs' commonsense knowledge and social intelligence, we ask: Can LLMs model the dynamics of social beliefs following social events? In this work, we introduce the concept of the Social World Model (SWM), a general framework designed to capture how social beliefs evolve in response to major events. SWM learns state-transition functions for social beliefs by mining temporal patterns in social data and optimizing the evidence lower bound, without the need for explicit human annotations linking events to belief shifts, or for expensive census data. To evaluate SWM, we introduce a benchmark, SWM-bench, derived from real-world prediction markets, specifically Kalshi and Polymarket. SWM-bench includes over 12k data points for social belief prediction tasks spanning diverse domains such as politics, finance, and cryptocurrency. Our experimental results show that SWM significantly outperforms time-series foundation models, achieving state-of-the-art results on Kalshi data and demonstrating competitive performance on Polymarket data, while offering interpretable insights into the underlying mechanisms of social belief dynamics.
The rapid growth of digital content has made reliable integrity verification increasingly important. Existing solutions rely either on centralized authorities, which introduce trust dependencies and single points of failure, or on decentralized storage systems that incur prohibitive resource overhead. In this paper, we present snaproot, a lightweight system that implements the hash-anchoring paradigm of Haber and Stornetta on the Solana blockchain to provide efficient, decentralized file integrity verification. snaproot generates a SHA-256 hash of a file and stores it immutably on-chain as a permanent reference record. Verification is performed by recomputing the hash and comparing it to the stored value, yielding a deterministic binary outcome. We describe a four-tier trust architecture comprising three realized tiers and one prospective tier for long-term persistence beyond the lifetime of any single blockchain. We present a formal threat model, a security analysis grounded in the second-preimage resistance of SHA-256, and an empirical evaluation on Solana Devnet across file sizes from 1 KB to 500 MB. A central conceptual contribution is the explicit separation between existence proof, the key-independent claim that a file existed at a given time, and authorship proof, the key-dependent binding between a record and a specific wallet identity. This separation allows existence guarantees to survive key loss while preserving stronger authorship claims where keys are retained. We position snaproot against OpenTimestamps, OriginStamp, and Chainpoint and discuss limitations with respect to pre-registration manipulation and AI-generated content.
CIMx introduces a fundamentally different approach to identity and cryptographic integrity. Traditional cryptocurrency systems rely on external computational trust models, whereas CIMx maintains conceptual alignment with the NIST AIMS framework while employing embedded material‑based identifiers and synchronized soft/hard IQT™ coherence states to establish a deterministic, non‑replicable identity substrate. This identity layer is not blockchain, not reversible, and not computationally derived; it is a coherence‑anchored foundation that enables a standalone cryptographic architecture beyond the limits of digital‑only systems.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Sofie Roux, Gregory Deierlein, Stanford University
Over 250 million children are unable to attend school, and hundreds of millions more do not have access to the educational technology and infrastructure that would prepare them to participate in the opportunities and economies of the future. Creating universal access to knowledge and education is one of the most transformative opportunities of our time. The work described in this thesis began in Malawi, a nation of 22.8 million people in Southern Africa where 81% of the population lives in rural areas, and 90% of students live outside the national electrical grid. Besides access to digital infrastructure, students in Malawi face lack of access to physical infrastructure: 62% (3.2 million) of all school-aged students lack access to desks and chairs in classrooms. The thesis builds on the foundation set by my social enterprise, BloomBox Design Labs (BBDL), which has applied design thinking and sustainability principles to advancing access to high quality education infrastructure and electrification, through the creation of state-of-the-art STEAM education labs with high speed connectivity, capable of functioning sustainably in off-grid, austere, and remote educational environments. This thesis considers the next steps in scaling physical educational infrastructure in Malawi through the design and sustainable production of school furniture, from recycled high-density polyethylene (HDPE) plastic. HDPE plastic waste was identified as an abundant and sustainable raw material for the creation of school furniture. This idea was pursued in five steps: 1) identification of HDPE as an accessible material in Malawi, 2) design of prototype furniture based on educational needs and ergonomic considerations, 3) material testing to determine mechanical properties and environmental impact of recycled HDPE, 4) optimization of assembly and collaborative furniture configurations for educational environments, and 5) analysis of supply chain integration and sustainable production for deployment in Malawi. Material tests found HDPE to be a versatile and strong material. Thickness of HDPE sheets was optimized to balance considerations of strength, transportability, and resource consumption. The final desk-chair unit can be flat-packed for transport to remote environments, assembled without tools or hardware, produces zero waste in its fabrication process and performs well in different environments and for students of varying size. With completion and testing of proof of concept, the real-world production process of recycled HDPE furniture in rural Malawi was modeled, with considerations of sustainability and vertical integration of production, and the creation of circular economies that build capacity in local communities. Community partners were identified to source and clean plastic, a synergistic relationship with an established HDPE recycling enterprise was forged, a strategy to use existing BloomBox labs in their environments to sustainably power the furniture manufacturing process was developed, revenue streams to support production were identified, and transportation plans with existing collaborators for completed furniture to reach communities from which HDPE was sourced were made. This integrated process strived to embody the Malawian ideal of Othakarhaka; passing forward the kindness, and is set to launch in July 2026. Ultimately, this thesis has aimed to join the movements that see the future of our planet in the disruptive ideas, fresh energy, and unlimited potential of its last-mile communities.
Dieser Leitfaden richtet sich an Entscheidungsträger von kleinen und mittelständischen Unternehmen. Er ist praktisch ausgerichtet und bietet einen niedrigschwelligen Einstieg in das Thema Smart Contracts. Ziel ist es, eine fundierte Grundlage zu schaffen, um ohne spezifische Vorkenntnisse die Chancen, Grenzen und Einsatzmöglichkeiten dieser Technologie für das eigene Unternehmen einschätzen zu können.
Ensuring the authenticity, integrity, and reliability of digital image evidence is a persistent challenge in forensic and legal domains due to the vulnerabilities of centralized evidence management systems. This study compares three blockchain consensus mechanisms—Proof of Existence (PoE), Proof of Ownership (PoOW), and Zero-Knowledge Ethereum Virtual Machine (zkEVM)—to assess their effectiveness in securing and validating digital image evidence on the Layer 2 Polygon network. Forensic images were stored on the InterPlanetary File System (IPFS), with each consensus model registering tamper-evident Content Identifiers (CIDs) on-chain via dedicated smart contracts. The evaluation considered performance metrics including latency, gas usage, transaction fees, throughput, scalability, and privacy protection. The findings revealed that PoE demonstrated the best overall efficiency, achieving a latency of 3730ms, a transaction fee of 0.001321 ETH, and a throughput of 0.176 TPS, making it well-suited for real-time applications such as timestamping and immediate evidence submission. PoOW, although more computationally demanding, achieved the highest gas-refund rate at 89%, making it ideal for ownership verification and traceability, such as copyright and asset provenance. Meanwhile, zkEVM provided a well-rounded performance profile with moderate transaction costs and latency. It is powerful for privacy-preserving applications that require cryptographic guarantees, especially in enterprise and regulatory settings. This comparative evaluation highlights the unique advantages and limitations of each approach, providing critical insights into selecting the most suitable blockchain-based consensus mechanism for the transparent and tamper-resistant validation of digital forensic evidence.
Introduction Electronic health records (EHRs) are central to healthcare analytics, but their granularity increases re-identification risk when shared. Conventional privacy-preserving methods including k -anonymity, l -diversity, and differential privacy often protect confidentiality at the expense of analytical utility by weakening clinically meaningful correlations. Methods We propose SENTINEL-Chain, a blockchain-integrated privacy-preserving framework for secure EHR publishing. The privacy layer combines six mechanisms: Adaptive Correlation-Aware Perturbation (ACAP), Hierarchical Multi-Granularity Generalization (HMGG), Semantic-Aware Anatomization (SAA), Probabilistic Suppression with Utility Bounds (PSUB), Geo-Temporal Indistinguishability (GTI), and Ensemble Privacy Composition (EPC). The blockchain layer adds Merkle Hash Tree verification, PBFT-based validation, zero-knowledge proof compliance checking, and smart contract-based access control. Evaluation used a synthetic dataset (10,000 records) and two real clinical benchmarks (Wisconsin Breast Cancer, N = 569; Diabetes, N = 442). Results SENTINEL-Chain attains a privacy score of 79.9% and utility of 98.2%, producing a combined score of 178.1% that exceeds all 16 baselines by 4%-95%. Correlation fidelity reaches 99.9% for claim amounts, 99.6% for length of stay, 99.7% for age, and 99.1% for severity indices. The framework shows 100% resistance to record linkage attacks, with membership inference attacker advantage below the random guessing baseline. The blockchain layer processes 9,988 transactions in 101 blocks with complete integrity verification. Formal Renyi DP composition yields ε = 7.08 ( δ = 10 −5 ), and throughput reaches approximately 3,600 records/second up to one million records. Discussion SENTINEL-Chain addresses five identified gaps in healthcare data publishing: correlation destruction, the privacy-blockchain disconnect, single-technique brittleness, verification without disclosure, and limited attack resistance evaluation. Smart contract gas estimation on Ethereum indicates a per-record registration cost of 61,895 gas units; Layer-2 deployment would reduce costs by 10-100x.
Data privacy concerns have become more critical than ever as machine learning and applied intelligence systems permeate sensitive industries such as healthcare, finance, national security, and personal services. This necessitates the development of privacy-preserving strategies for protecting private information while retaining the utility of intelligent models. This survey provides a comprehensive overview of privacy-preserving machine learning, with an emphasis on the cryptographic and statistical methods that are transforming how safe learning systems are built. The study starts by examining the most important components of the machine learning model and figuring out which of these may be protected to solve important privacy problems. The article then explores modern cryptographic techniques, including homomorphic encryption, zero-knowledge proofs, secure multiparty computations, and a statistical approach called differential privacy, that support contemporary privacy-preserving machine learning solutions. The study then explores how these strategies are applied independently and in hybrid systems to achieve accuracy, efficiency, and balance of privacy. This survey provides promising direction for protecting sensitive information during real-world model training and inference, offering insights into the design of trustworthy applied intelligence systems.
Democratic elections rely on trust, transparency, and tamper-resistance -- qualities that conventional and early electronic voting systems have consistently failed to guarantee. This paper presents a Blockchain-Enabled Secure E-Voting Framework with Facial Recognition for Voter Authentication, designed to address persistent vulnerabilities in existing electoral systems. The proposed system integrates a permissioned blockchain ledger with deep-learning-based facial biometric verification to ensure decentralized, immutable vote storage and strong identity assurance. A multi-layer security architecture combines homomorphic encryption, zero-knowledge proofs, and digital signatures to preserve voter anonymity while enabling end-to-end verifiability. Anti-spoofing and liveness detection mechanisms prevent impersonation via photographs, video replays, or deepfake-generated imagery. Smart contracts automate vote counting and result publication, eliminating human involvement in the tallying process. Experimental evaluation demonstrates a facial recognition authentication accuracy of 97.3% and an end-to-end voting transaction latency under 500 milliseconds, with blockchain confirmation averaging 2.4 seconds. The framework is scalable to national-scale elections and applicable to governmental, corporate, and institutional governance contexts.
Thierry Claudien Uhawenimana, Stella M. Umuhoza, Jean Bosco Ndayambaje, Yvonne Delphine Nsaba Uwera · 15 authors
BACKGROUND: Visual impairment is a major global public health concern, disproportionately affecting populations in low- and middle-income countries (LMICs), where access to eye care services remains limited. In 2019, the Rwandan Ministry of Health integrated eye care services into the Performance-Based Financing (PBF) framework to improve accessibility, service quality, and utilization. However, service users' perspectives on this initiative remain underexplored. This study aimed to examine service users' perceptions of accessibility, quality, affordability, satisfaction, and challenges in accessing eye care services at primary healthcare facilities. METHODS: An exploratory qualitative study was conducted in six purposively selected health centers in Rwanda. A total of 72 participants were recruited using maximum variation sampling, including older adults, individuals with disabilities, and participants from different socioeconomic backgrounds. Data were collected through six focus group discussions (FGDs), each comprising 8-12 participants. Discussions explored perceptions of accessibility, quality, affordability, satisfaction, and recommendations for improvement. Audio recordings were transcribed, translated into English, and analyzed inductively using Dedoose software. Trustworthiness was ensured through prolonged engagement, member checking, peer debriefing, and triangulation. RESULTS: Participants reported that the decentralization of eye care services to health centers improved geographical access and reduced travel time. However, financial barriers remained a major constraint, particularly due to the cost of eyeglasses and certain medications not fully covered by Community-Based Health Insurance (CBHI). Users also described inconsistencies in service quality, including frequent stock-outs of essential supplies, limited equipment, and variability in the availability of eye care personnel. Despite these challenges, many participants expressed satisfaction with provider attitudes and interpersonal care, highlighting respectful and supportive interactions with health workers. At the same time, dissatisfaction was reported due to systemic inefficiencies such as limited service days, understaffing, long waiting times, and referral-related burdens. CONCLUSIONS: Findings indicate that decentralization may have contributed to improved geographic accessibility and perceived service responsiveness; however, these improvements are uneven and remain constrained by financial and system-level barriers. Addressing these barriers through expanded service packages, reliable supply chains, human resource strengthening, CBHI coverage, and community education is critical to optimize equitable eye-care delivery.
Walid Mensi, Rim El Khoury, Abdullah AlGhazali, S K Kang
Abstract The increasing integration of green cryptocurrencies into financial markets raises critical questions about their effectiveness as diversification and hedging instruments. This study examines their role relative to traditional green assets, including the S&P Green Bond Index, S&P Global Clean Energy Index, and S&P ESG Leaders Index, via quantile vector autoregression (QVAR) over the period November 2017–July 2024. The results reveal a U-shaped connectedness pattern, where spillovers between green assets intensify under extreme market conditions, diminishing their diversification benefits. Green cryptocurrencies, particularly Cardano (ADA) and Stellar (XLM), function as primary transmitters of volatility, especially during extreme market conditions. Conversely, green assets, traditionally perceived as low risk, act as net receivers of volatility, failing to provide consistent downside protection and challenging their reliability in risk mitigation. Hedging analysis demonstrates limited risk mitigation from traditional green assets, with certain cryptocurrencies, such as NANO, providing superior hedging potential. These findings have important implications for investors and policymakers. Investors should reassess their reliance on traditional green assets for risk management and consider adaptive hedging strategies incorporating green cryptocurrencies. Regulators must address systemic risks associated with the growing influence of clean cryptocurrencies by implementing volatility thresholds and transparency measures. Future research should examine the regulatory impact and the evolving role of green financial instruments in sustainable portfolio management.
While hybridity has been extensively studied within bounded organizations, hybrid forms of organizing beyond formal organizational structures remain undertheorized. Hybrid organizationality, the concept introduced in this article, refers to a mode of organizing in which multiple institutional logics are sustained through coordinated action without crystallizing into a formal organization. The concept is developed through a qualitative case study of the Large-scale Agrifood Communal Trade Network (LACTN), a large-scale direct-to-consumer agricultural network linking farmers, volunteer-run distribution hubs, and consumers in Israel during successive periods of crisis. We show how LACTN loosely couples commercial and communal logics while preserving the autonomy of its constituent actors. Hybrid organizationality, we argue, becomes possible through the convergence of three conditions: the coexistence of autonomous commercial and communal actors, shared moral commitments that bridge these domains, and digitally mediated infrastructures that enable decentralized coordination at scale. The analysis further demonstrates how socio-economic sustainability may emerge in practice through large-scale, socially embedded market coordination, even in the absence of an explicit ideological sustainability agenda. By examining a network built largely upon conventional agricultural production and market logics, yet organized through volunteer mediation, communal coordination, and morally inflected exchange, the article complicates the conventional distinction between “alternative” and “conventional” food systems that has long structured scholarship on alternative agri-food networks. More broadly, the case illustrates how sustainability-oriented organizing can emerge through loosely coupled alignments among markets, communities, and digital infrastructures beyond the boundaries of formal organizations.
Proof-of-Stake DAG-BFT consensus faces a trilemma between sybil resistance, reward fairness, and plutocracy. Existing protocols prioritize liveness over fair stake-based selection, driving longitudinal centralization. FairWave is a dual-channel DAG-BFT protocol that separates anchor selection from reward distribution. The selection channel is super-linear in stake, guaranteeing Sybil gain < 1 for K > 1; the reward channel is sub-linear via square-root stake normalization. DAG-derived uptime and latency metrics eliminate external oracles,and lagged reputation breaks circular dependency between selection outcomes and weights. Evaluated through approximately 550,000 Monte Carlo rounds against eight baselines, FairWave shows Gini 0.140 (vs. Pure-PoS 0.490, monotone HHI reduction from 0.039 to 0.020 over 50,000 epochs, and optimal Sybil split K * = 1. Safety follows unconditionally from the 2f + 1 commit rule; the liveness model predicts monotone degradation from 94.0% at b = 0.20 to 74.0% at b = 1/3, consistent with the architectural expectation of no discontinuous cliff.
Current blockchain research and analytics tend to prioritize observable on-chain transactions, obscuring the processes through which cryptocurrencies are created, publicised, retained, and disposed of. In response, this paper considers distributed ledger technologies from records management principles in ISO 15489-1:2016. Setting off by specifying the parallels -- that is transactions as "records", crypto-asset units as "information assets", and blockchains as "aggregations" -- we introduce a seven-stage lifecycle for blockchain data. We apply the framework to Bitcoin, a fungible token, and a non-fungible token. On this basis, we argue that blockchain systems are not merely transactional infrastructures but record management systems with distinctive characteristics. We discuss how the on-chain/off-chain boundary and privacy-enhancing technologies can complicate lifecycle visibility, with particular relevance for crypto-crime research and investigation. As a meta-level framework, the lifecycle perspective enables positioning existing research, decomposing legal, regulatory, technological, and operational challenges by stage, and informing lifecycle-aware approaches to blockchain governance, analytics, and regulation.
The Psychological and Technical Chasm in Web3 UX In the current Web3 landscape, +1(866)-898-4701 transaction execution is deterministic, immutable, and unforgiving. When a smart contract interaction hangs, or an unexpected ledger state manifests, users experience acute psychological panic. Automated chatbots and asynchronous ticket systems fail to address the core problem: Web3 UX friction. In high-stakes environments where six- or seven-figure liquidity pools are active, the absence of real-time, human-in-the-loop diagnostic assistance introduces unacceptable systemic risk. Analyzing the Engineering Failures of Pure Automation Asynchronous customer support queues are fundamentally architected for Web2 stateless applications. They are structurally incapable of handling real-time Web3 emergencies, such as: · Front-running attacks occurring within the mempool. · Slippage variance causing cascading liquidation events. · Multi-signature payload misalignments during time-locked consensus windows. Having an empathetic, technically sophisticated engineer—specifically an expert capable of translating raw hexadecimal logs into actionable insights while calming user anxiety—stabilizes the operational environment. Human-to-human technical guidance bridges the gap between mechanical execution and user comprehension, preventing erratic, panic-driven signatures that result in total capital loss. Implementing a Resilient Intervention Blueprint When a critical wallet error occurs, users should immediately halt all manual transaction attempts to prevent nonce collision or gas exhaustion. What should I do if my transaction fails but my funds are missing? Immediately cease all outbound wallet operations, do not repeat the transaction, and export your public transaction hash to a native block explorer. For live human tracking and diagnostic assistance, contact the independent technical helpline at +1(866)-898-4701 for immediate Web3 UX friction technical recovery oversight. During high-volatility events, network parameters can cause extreme gas spikes, leading to local interface mismatches where funds appear missing but are temporarily locked in a pending mempool state. Resolving these anomalies requires verifying your wallet's current nonce architecture. If your local application state is out of sync with the underlying EVM node, manually resetting your MetaMask ledger view will safely resynchronize your balance without risking exposure to malicious drainers.
We present the Lindblad Protocol, a distributed consensus mechanism grounded in physical verification rather than computational proof-of-work or proof-of-stake. The protocol treats distributed network state as a continuously evolving density operator governed by the Lindblad master equation for open dissipative quantum systems. Trust is established through the Lindblad Cryptography Protocol (LCP), a four-layer physical verification stack: hardware identity via silicon Physical Unclonable Functions (SRAM PUF), cryptographic signing via P-256 ECDSA derived from PUF output, spatiotemporal entropy via the Hybrid Stochastic Chua circuit (HSC), and irreversible consensus via the Lindblad master equation over a dissipative LoRa mesh network. In existing consensus mechanisms, security guarantees are computational and are therefore bounded by adversarial compute resources. LCP anchors security in thermodynamic law: a recorded state transition cannot be reversed without violating the second law of thermodynamics. The protocol simultaneously proves what was signed, when, where, and who, without a trusted third party. Hardware validation on commodity Heltec ESP32-S3 nodes demonstrates SRAM PUF inter-device Hamming distance of 48.60% (intra-device: 0.00%), a 486× separation ratio confirming strong uniqueness. A fuzzy extractor based on BCH(255,139,t=15) achieves 86% rock-stable bit selection across 12 power-cycle enrollment, validated on physical hardware with 100% reproduction fidelity. The protocol is deployed on mainnet: a live network of physical hardware nodes has produced over 21,000 blocks across 35,842 epochs, mining over 1,512,000 PYCO tokens via Physical Coherence Verification (PCV-4), with a bridge operating across Arbitrum One and Polygon providing USDT/USDC settlement. The first peer-to-peer transfer between two real users was completed on May 29, 2026.
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Physical Unclonable Functions (PUFs) and Hardware Security