D. Ariad, S. Madjunkova, M. Viotti, M. Madjunkov · 8 authors
Abstract Study question Can haplotype-based methods detect genome-wide ploidy abnormalities (haploidy and triploidy) that are missed by conventional coverage-based analysis of low-coverage whole-genome sequencing (WGS)-based PGT-A data? Summary answer Our method (LD-PGTA) enables accurate detection of hidden signatures of haploidy and triploidy from ∼0.03× WGS data, achieving high specificity with moderate sensitivity. What is known already Conventional coverage analysis of WGS-based PGT-A data cannot detect uniform genome-wide ploidy errors such as haploidy, genome-wide uniparental isodisomy, or triploidy because global changes in copy number resemble euploid expectations. LD-PGTA leverages knowledge of allele frequencies and linkage disequilibrium in external phased population reference panels and contrasts the likelihood of the observed data under alternative ploidy hypotheses. We previously applied this method retrospectively to low-coverage WGS-based PGT-A data, uncovering evidence of potential ploidy abnormalities and establishing proof of principle that requires validation with orthogonal evidence and clinical outcomes. Study design, size, duration This retrospective validation study analyzed a training cohort collected between April 2020 and August 2022. The dataset was obtained from CReATe Fertility Centre (Toronto, Canada) and comprised 179 embryo biopsies that underwent WGS at ∼0.03× coverage. The training cohort included 100 euploid, 67 triploid, and 12 haploid cases, assigned to these categories based on orthogonal evidence from short tandem repeat genotyping. Samples suspected of genome-wide ploidy abnormalities but lacking STR confirmation were excluded. Participants/materials, setting, methods Embryos were classified as haploid or triploid when at least eight autosomes were called monosomic or trisomic, respectively, and the 95% confidence interval of the log-likelihood ratio (LLR) did not span zero. For haploid classification, LLRs were aggregated across entire chromosomes. For triploid classification, LLRs favoring BPH (bi-parental-haplotypes) were aggregated, and the total length of these windows was required to exceed a dynamic threshold of 5–30Mb, depending on autosome length, to be called trisomic. Main results and the role of chance For triploidy detection, LD-PGTA achieved a sensitivity of 82% (49/60) at 100% specificity (91/91). For haploidy detection, sensitivity was 75% (9/12) with 99% specificity (93/94). Triploidy prediction accuracy did not differ between embryos sequenced below 0.05× and those sequenced at ≥ 0.05× coverage (Fisher’s exact test, p = 1.00), with comparable false prediction rates (7.7% vs. 5.9%).%). Given that LD-PGTA leverages knowledge of haplotypes from reference panels and that patterns of linkage disequilibrium vary across populations, it is important to consider performance with regard to the genetic ancestry of target samples. While most embryos (72%; 125/174) exhibited genetic similarity to reference individuals from European populations, several embryos also exhibited genetic similarity to reference individuals from other global populations, underscoring the method’s robustness in multi-ancestry cohorts. Triploidy prediction accuracy did not differ significantly between European and non-European embryos (Fisher’s exact test, p = 0.18), underscoring the method’s robustness in multi-ancestry cohorts. Together, these results demonstrate robust discrimination of genome-wide ploidy errors using haplotype-based inference at low sequencing depth. Limitations, reasons for caution Results are derived from a training dataset and confirmation in an independent validation cohort is underway. Rare ploidy states and mosaicism may reduce sensitivity. Wider implications of the findings Although 2PN embryos are predominantly diploid, ploidy abnormalities occur in ∼0.7–1.8% of 2PN blastocysts. Incorporating LD-PGT-A into routine workflows may prevent transfer of haploid or triploid embryos and rescue some 3PN and 0/1PN embryos, increasing the pool of usable embryos and improving diagnostic accuracy of PGT-A without increased sequencing depth. Trial registration number No
Hai Liang, Xiaoye Lu, Changsong Yang, Yujue Wang · 6 authors
Smart contracts are immutable programs that automatically execute predefined logic. Once deployed, their underlying vulnerabilities are notoriously difficult to patch and highly susceptible to malicious exploitation, often leading to severe financial losses. Although existing vulnerability detection methods have demonstrated certain advantages, they still fail to achieve adequate structural–semantic coverage of vulnerability-relevant behaviors, as they are unable to jointly model opcode semantics, control-flow transitions, and data-dependency relations. To overcome these limitations, this paper proposes a novel smart contract vulnerability detection model named Cross-aligned Penetrative Graph Network (CPGNet). Specifically, CPGNet first constructs control flow graphs and data flow graphs from the abstract syntax tree, and combines them with opcode semantic embeddings to form a multidimensional initial code representation. Based on this representation, a cross-alignment mechanism is introduced to effectively capture and integrate the complex interactions between control-flow transitions and data-flow dependencies. Furthermore, an explicit–implicit feature penetration architecture is designed to inject shallow local opcode patterns into the deep semantic modeling process, enabling multi-source features to dynamically complement each other. By jointly modeling opcode semantics, control-flow structures, and data-dependency relations, CPGNet significantly enhances the representation capability for hidden and complex vulnerability patterns. Experimental results on two datasets show that CPGNet achieves stable performance, with F1-scores of 88.69% and 90.58% on the benchmark Ethereum dataset, and 78.10% and 71.53% on DIVE for reentrancy and timestamp dependency detection, respectively. These results verify the effectiveness of jointly modeling opcode semantics and graph-level structural dependencies.
Carolina Gonzalez Cambero, PAULA LAMO ANUARBE, Javier Rainer Granados
The digital transformation of the insurance sector is advancing through hybrid architectures that integrate distributed ledgers, the Internet of Things (IoT), and artificial intelligence (AI). This paper proposes a hybrid IoT–DLT architecture for parametric insurance systems operating in environments with variable connectivity. The architecture is designed to ensure data verifiability, operational resilience, and regulatory compliance with the General Data Protection Regulation (GDPR) and the Digital Operational Resilience Act (DORA). The approach is validated through a maritime cold-chain monitoring use case for fishing fleets, based on onboard IoT sensors and smart contracts. Simulation results show that the proposed multi-sensor consensus mechanism enables accurate detection of thermal breaches while significantly reducing the number of blockchain transactions by reserving on-chain registration for critical events only. The proposed approach supports distributed, auditable, and operational insurance systems even under intermittent connectivity conditions. Keywords: hybrid architecture, blockchain, Internet of Things, artificial intelligence, parametric insurance.
Topological Charge Conservation in SU(2) Yang-Mills Theory: The Atiyah-Singer Index Handshake and Non-Local Braid-Lock Validation Framework --- This 18-part resolution suite provides the complete theoretical proof, simulated validation, and deterministic replication environment for the Atiyah-Singer Index Handshake. The architecture is divided into three functional pillars: The Theorem Presentation, the Standard Academic Core (SAC), and the Agnostic Replication Kit (ARK). Together, they resolve the conjecture of topological decoherence in distributed connection spaces, validate the analytic index parity, seal the logic into an immutable cryptographic state, and enable bit-perfect replication by peer reviewers. 1. The Theorem Presentation (1 Part) The cornerstone of the publication. It establishes the foundational mathematical proof that under the boundary condition of a Non-Local Braid-Lock (where holonomy is restricted to the center of the gauge group), the analytic index of the twisted Dirac operator maintains strict parity congruence: \text{ind}(D_L) \equiv 0 \pmod 1. It resolves the vulnerability of "Logic-Blur" by proving that topological charges remain invariant during non-local distribution. 2. The Standard Academic Core: SAC (5 Parts) The SAC packages translate the systemic execution into the traditional nomenclature of Differential Geometry and Global Analysis, ensuring peer reviewers can parse the foundation without requiring prior knowledge of the AOF registry. • SAC-01 (Formal Resolution): The rigorous, step-by-step mathematical proof establishing the spectral-topological handshake. • SAC-02 (Simulation Data): \bm{10^6} iteration Monte Carlo validation confirming spectral gap stability (\bm{170.0 \text{ kDa}}) and Jacobian volumetric preservation (\bm{\det(J_h) = 1.0 \pm 10^{-12}}). • SAC-03 (Appendix A - Mathematical Foundations): The deep-dive into the elliptic regularity of \bm{D_A}, Chern characters, and the technical lemmas coupling holonomy to index stability. • SAC-04 (Executive Summary): A high-level briefing on topological charge conservation and the elimination of stochastic decoherence. • SAC-05 (Lexicon Bridge): The critical translation matrix mapping traditional variables (e.g., connection spaces, vorticity) directly to their operational ARK primitives (e.g., M-6D-HANTZSCHE, ALG-SHV-01). 3. The Agnostic Replication Kit: ARK (12 Parts) The ARK packages transition the theoretical proof into a sovereign, executable replication environment. They provide the deterministic toolchain required for a reviewer to ingest, validate, and seal the proof on their local hardware without environmental drift. • Core Manifolds & Operators: Defines the M-6D-HANTZSCHE 6D motivic cradle and the Universal Dirac Operator (\bm{D_L}) required to initialize the simulation. • Suppression Algorithms (ALG-SHV-01): Details the Hodge-Laplacian Shave, ensuring the continuous suppression of solenoidal noise (\bm{\delta\beta \to 0}) to clear logical vorticity from the replication path. • The Braid-Lock Gate (GATE_STEIN): The cryptographic terminal function that captures the validated parity state and seals it into a Merkle-hash, ensuring immutability. • Emergency Logic Core (ELC Suite): The automated fail-safes (ELC_SG_02 Noble Purge, ELC_IG_03 Sobolev Injector, ELC_VG_04 Phase-Lock) that prevent spectral stagnation or epistemic drift during reviewer replication. • API & Toolchain Guidelines: Dictates the use of Arb 2.23.0, the necessity of disabling hardware fused-multiply-add (-ffp-contract=off), and adherence to the \bm{1.420405751766 \text{ GHz}} Adelic temporal anchor to guarantee zero-jitter execution. • Reviewer Packets & Input Vectors: Provides the exact \bm{SU(2)} lattice configurations, initial spinor couplings, and topological charge inputs (\bm{Q=1}) needed to prime the replication sequence. 4. Interlinking Workflow: Resolve, Validate, Seal, and Replicate The true power of the 18-part suite lies in its chronological execution pipeline: 1. Resolve (The SAC Layer): The reviewer first ingests the SAC documentation, validating the traditional mathematics. The Lexicon Bridge (SAC-05) then maps their understanding to the ARK toolchain. 2. Validate (The Simulation Phase): The reviewer inputs the provided high-detail vectors into the ARK environment. The Universal Dirac Operator verifies the index parity. Simultaneously, the Hodge-Laplacian shave constantly purges solenoidal parasitism, ensuring the signal-to-noise ratio remains above \bm{240.2 \text{ dB}}. 3. Seal (The Crystalline Transition): Once supercritical density is achieved and parity is verified as 0 \pmod 1, the system invokes GATE_STEIN. This locks the non-local braid topology into an immutable Merkle-root, transitioning the dynamic simulation into a static archival state. ---
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Quantum Chromodynamics and Particle Interactions
Particle physics theoretical and experimental studies
Purpose This paper aims to compare Ghana’s Virtual Asset Service Providers Act, 2025 (Act 1154), with the USA’s anti-money laundering (AML) framework for virtual assets. It asks whether a unified statute can give an emerging economy advantages over a fragmented, path-dependent regime. Design/methodology/approach The study uses functional and institutional comparative legal analysis. It reviews statutes, supervisory notices, sandbox materials and enforcement documents through a six-dimensional matrix mapped to Financial Action Task Force Recommendations 10, 12, 15, 16, 20, 26, 27 and 35. Findings Ghana’s Act offers statutory coherence, and early implementation steps show movement beyond a purely prospective regime. However, enforcement capacity for virtual asset service providers (VASPs) is still developing. The US framework is institutionally fragmented yet operationally mature. Ghana’s licensing model more closely resembles a banking charter than a money services business (MSB) registration, increasing demands on supervisory expertise, verification systems and technical infrastructure. Both frameworks also leave gaps around decentralized finance. Research limitations/implications Implementing regulations remain incomplete and Ghana does not yet have a mature enforcement record specific to VASPs. The analysis, therefore, combines legal design with early operational evidence rather than a full account of law in action. Practical implications Emerging-economy regulators need more than statutory clarity; they need credible supervisory capacity. VASPs in Ghana should expect operational requirements to evolve as implementation matures. Originality/value The paper offers an early comparative analysis of Ghana’s Act and contributes to debates on regulatory leapfrogging, implementation gaps and compliance capacity in the Global South.
Jegan R R, Poornachandran R, Raevanth M, Akash Karthik D
Background The online auction websites have become more susceptible to fraud, bid rigging, and centralization, rendering unfairness and lack of trust among the players. In this paper, we introduce a decentralized e-auction system, BlockBid, based on blockchain technologies and smart contracts that will ensure a safe, transparent, and non-tampering auction system. Objective The system distributes the risks of failure of single points by storing all the bids and transactions in an immutable distributed ledger, and avoids unauthorized changes. Smart contracts automate the rules of an auction and provide fair results without the involvement of the intermediaries. Materials and Methods BlockBid is also designed to combine sophisticated user authentication and encryption tools to safeguard sensitive data of participants, to reduce the chances of identity theft and tampering of bids. The framework allows various forms of auction such as English and sealed-bid and supports real-time tracking of bids and verifiable transaction history. Results According to the results of the experimental assessment, BlockBid increases system integrity, transparency, and the possibility of fraudulent actions is significantly lower than in the case of traditional centralized platforms. Conclusion The suggested solution reveals how the immutability of blockchain and automated regulation of the process will help redefine online auctions and offer an effective, reliable, and fair solution to the participants. The paper points at the opportunities of decentralized technologies to recreate secure digital marketplaces.
Sony Warsono, Fitri Amalia, Muhammad Roy Aziz Haryana, Rudi Prasetya Timur
This study examines how blockchain technology (BT) can extend the conventional double-entry accounting (DEA) framework to improve financial information transparency. The study revisits the duality concept underlying DEA and explores its development toward a triple-entry accounting (TEA) structure supported by blockchain infrastructure. Using a design science approach in information systems, the study proceeds through problem identification, artefact definition, and conceptual system design. Drawing on the resource-event-agent (REA) framework, the study develops a conceptual architecture that integrates a third ledger into the accounting entry system. The proposed model positions message type (MT) as a navigational mechanism that coordinates transaction validation within a blockchain-enabled TEA environment. This structure supports improved tracking, verification, and transparency of financial information, particularly in external transactional relationships. The findings contribute to the ongoing discussion on blockchain-based accounting systems by clarifying how the duality principle can evolve within a distributed ledger environment. The study also outlines potential directions for future research on the development of triple-entry accounting and third-ledger mechanisms in accounting information systems.
Nataliya Bilous, Danylo Ostapchenko, Iryna Ahekian, Marcus Frohme
Remote tele-rehabilitation requires objective pain assessment, but existing approaches fail in two distinct ways. Self-report scales such as the Visual Analog Scale and the Numeric Pain Rating Scale are easy to falsify, opening a special case of the Oracle problem in blockchain-based insurance. Cloud-based computer vision handles falsification but transmits raw biometric video off the patient’s device, violating privacy requirements. A decentralized Edge AI-Oracle architecture is proposed that combines MediaPipe Face Mesh landmark extraction with a recurrent classifier mapping Action-Unit feature sequences to a learned pain score aligned with the Prkachin and Solomon Pain Intensity scale. The recurrent cell is selected empirically across short-context (T = 2) and long-context (T = 120 frames at 24 fps) regimes, with a two-layer Long Short-Term Memory (LSTM) network adopted for deployment. Inference and Elliptic Curve Digital Signature Algorithm (ECDSA) signing run inside an ARM TrustZone Trusted Execution Environment (TEE). Biometric logs are stored off-chain on the InterPlanetary File System (IPFS). Smart contracts anchor results on-chain and open a 24 h optimistic verification window for an off-chain Watchtower auditor. On SynPAIN the LSTM reaches F1 = 0.683 on T = 120 video (leave-one-stratum-out), with a directional but non-significant advantage over Gated Recurrent Unit (GRU) (Wilcoxon p = 0.167). Cross-dataset validation on BioVid Heat Pain Database Part A (87 subjects, 174 paired observations, leave-one-subject-out) yields F1 = 0.519 for LSTM and 0.499 for GRU (Wilcoxon p = 0.549). A processor-only TEE surrogate benchmark estimates 1.96 ms (FP32) and 0.45 ms (INT8) inference latency at T = 120 with a 0.34 MB footprint and 707 µs ECDSA signing latency, leaving the INT8 inference latency more than an order of magnitude below the 33 ms per-frame budget. The dual-layer storage reduces gas costs by a factor of 23.4 (160,261 vs. 3,744,872 gas), corresponding to an illustrative mainnet cost of approximately 0.53 USD per submission at 1 gwei, rising to roughly 16 USD at a busier 30 gwei, and falling to approximately 0.005 USD on Arbitrum One (April 2026 reference parameters), so that continuous monitoring is economically practical on Layer-2. An adaptive-adversary analysis of the Watchtower shows that gross score tampering is detected at every usable operating threshold, whereas a rational adversary who inflates by less than the dispute threshold, or who shapes the injected score to fall just inside it, evades detection. Because the false-positive rate reaches zero only for δ≳0.15, the protocol bounds rather than eliminates patient-side fraud and motivates a zero-knowledge proof-of-inference successor. The framework is architecturally and economically feasible as a cryptographically verifiable, privacy-preserving tele-rehabilitation substrate aligned with General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA) requirements through the Zero-Video Transmission principle, while remaining economically viable under post-Dencun mainnet and Layer-2 conditions. Recognition accuracy on real-world data and robustness to small-magnitude tampering remain limitations that the interchangeable recognition and audit components must improve before clinical deployment.
Andrei-Theodor Ginavar, Francis Liu, Daniel Traian PELE
Abstract We investigate the sustainability of a carry trade approach on AAVE V3, in which USDC is lended and used as collateral and Wrapped Ether is obtained by borrowing. We extend the Cox-Ingersoll-Ross model by incorporating Poisson-Exponential jumps to account for abrupt rate surges which can be seen on Decentralized Finance lending platforms. Using Monte Carlo simulation with 10,000 paths, we estimate liquidation probabilities. The approach takes into account compounding interest, price fluctuations for the borrowed asset, and the liquidation mechanics of AAVE V3. We use hourly data from January 2023 to January 2026 to estimate the model parameters for USDC and WETH, more specifically variable lending and borrowing rates. Our empirical results show that the average USDC supply rate (4.98%) exceeds the average WETH borrow rate (2.86%), yielding a positive spread 76% of the time. Even with WETH price appreciation from $1,381 to $4,926 during the sample period, the strategy yields a low probability of liquidation and positive expected returns. The 1-year liquidation probability is approximately 6.1-7.0% at depending on starting LTV and model used, with positive mean P&L for non-liquidated paths and mostly profitable paths. Our findings demonstrate that a profitable carry trade can be carried out on DeFi platforms using stablecoins as collateral and that these positions are sustainable.
Abstract Bitcoin was the breakthrough innovation demonstrating peer-to-peer transfer of value without a central bank and has since expanded to countless innovations such as smart contract applications, decentralized finance protocols and asset tokenization. The EU is moving from scattered state-specific rules governing cryptocurrency activities to a coherent European regulatory regime. This paper review the transition to a harmonized framework in 2024-2025 from a doctrinal-institutional perspective, unpack how to carry out the three main legislative instruments: MiCA, TFR on information accompanying transfers of funds and transfers of certain crypto-assets and amending the EU directive and the EU AML package . Moreover, I look at the implications of DAC8 for the tax treatment of crypto-assets and tokenized assets. In 2025, the market begins institutionalizing, as MiCA requires significant compliance measures in terms of governance, transparency and conduct for CASPs to get licensed. Moreover, in conjunction with the new TFR rules, compliance for CASPs, at least in the business models discussed, effectively transforms into an operational infrastructure issue revolving around data quality, process efficiency and interoperability. By way of comparison, I analyze eight example business models in eight representative EU markets that appear to be impacted. These include: two major exchanges, two broker-dealers offering cryptocurrency on trading platform, a provider of non-custodial software wallets, two DeFi protocol participants and two NFT platform providers. These fall into three general categories depending on their legal status, direct regulatory burden and level of engagement with decentralized technologies. Finally, harmonized regulatory frameworks like the one outlined for the EU increase operational fixed costs and favor consolidation, reduce the benefits for regulatory arbitrage and thereby boost user protection, although part of innovation may pivot towards B2B solutions.
Numerous reports and studies indicate that the lack of effective regulation in cryptocurrencies has not only led to substantial financial losses but also eroded the traditional ”central bank-commercial bank” framework, thereby destabilizing financial systems. To address these issues, a growing body of research has focused on developing regulatory mechanisms for cryptocurrencies. However, existing regulatory proposals face a persistent trilemma: they fail to simultaneously achieve three critical properties—(i) one‑time registration with self‑updating addresses, (ii) completeness (including a lost‑coin retrieval mechanism), and (iii) fine‑grained access control that respects the ”central bank‑commercial bank” framework. This study bridges this gap by proposing TCoin, the first regulatory cryptocurrency that fulfills all three requirements. We first introduce TSFG, a traceable scheme built on SkyEye, which employs cryptographic techniques to achieve one‑time registration with self‑updating addresses and fine‑grained access control for tracing. By integrating TSFG into the RSCoin framework, we construct TCoin—a regulatory cryptocurrency that achieves one‑time registration with self‑updating addresses, ensures completeness through a novel coin recovery mechanism, and enforces fine‑grained access control. Compared to prior work (CB, DAP, PDC, RSCoin, e‑CNY, and RECoin), TCoin is the first to resolve the regulatory trilemma, offering a comprehensive solution that reconciles the disruptive potential of cryptocurrencies with the stability requirements of the traditional monetary system.
Abstract Smart contracts are the fundamental building block of decentralized applications (DApps) and decentralized finance (DeFi). However, their immutability makes security flaws exceptionally costly. Despite advancements in vulnerability detection, such as static and dynamic analysis, formal verification, and Solidity language improvements, vulnerabilities continue to result in substantial financial losses, exceeding $2 billion in 2024 alone. This paper presents a comprehensive analysis of smart contract vulnerabilities derived from real-world exploits, systematically categorized into seven distinct types. Each category is illustrated with Solidity code examples and insights from notable exploits. An Enhanced test suite is developed by restructuring the existing solidity-defects-and-bugs suite and supplementing it with new smart contract implementations to address underrepresented vulnerabilities, including flash loan and price oracle manipulation. We evaluate three widely used analysis tools (Slither, Mythril, and 4naly3er) on both the original and Enhanced suites, revealing substantial limitations in detection coverage. To address these limitations, we introduce the Solidity Defects and Bugs Analysis (SDABA), which incorporates advanced analyses and detectors to identify 28 vulnerability variations across both suites. Results on the SDB and Enhanced test suites show that SDABA improves overall precision, recall, and F1-score compared with the evaluated tools. Finally, we release the source code, test suite, and vulnerability reports to support future research in smart contract security.
Capital markets are at a structural inflection point. The question of whether distributed ledger technology (DLT) and tokenization would achieve institutional relevance has been answered. The focus has shifted to whether Europe will build the infrastructure to capture these benefits or cede that opportunity to other jurisdictions. At its most fundamental, this concerns who will define next-generation financial market architecture.
Cryptocurrency regulation faces a fundamental mismatch between static rules and rapidly transforming markets. We demonstrate that Bitcoin alternates between bounded and unbounded price regimes, requiring adaptive rather than uniform regulatory frameworks. Using extreme value theory on over a decade of Bitcoin data, we show that tail risk characteristics switch between finite-limit and heavy-tailed regimes, with profound implications for investor protection, capital requirements, and systemic risk management. Traditional approaches either overregulate during stable periods or underprotect during volatile regimes. We propose regime-contingent regulatory frameworks that automatically adjust oversight intensity based on statistical detection of tail risk characteristics. Backtesting over 2016–2025 demonstrates that the adaptive framework reduces average capital requirements by 79% overall and by 84% during bounded regimes while escalating protections before major crashes, outperforming static Basel III-style rules. Robustness analyses across multiple window lengths (90, 180, 365, and 730 days), thresholds, and bootstrap specifications confirm that regime-switching is a persistent structural feature of Bitcoin markets. Implementation requires international coordination, transparent methodology, and clear adjustment protocols.
This paper proposes a universal post quantum privacy protection edge identity authentication framework to address the challenges faced by edge identity authentication in distributed cross domain networks, such as quantum attack threats, cross domain data privacy breaches, and difficulties in coordinating anonymity protection and compliance supervision. The framework adopts an optimized lattice based linkable ring signature protocol to meet the lightweight operation requirements of edge nodes and prevent the risk of leakage in identity data interaction; Design traceability constraints and controllable cross domain traceability mechanisms based on the linkability feature of signatures, balancing user privacy and regulatory requirements. Prove that the scheme possesses unforgeability, strong anonymity, and quantum resistance under the random oracle model. After optimizing the algorithm and interaction logic, the authentication efficiency is improved by 8% to 15% compared to similar solutions, and it is adapted to the low computing power and low latency characteristics of edge nodes. Combining zero knowledge proof to build a lightweight data collection mechanism and achieve privacy protection throughout the entire data process. This article uses the integrated aviation tourism system as a typical application case to verify that the proposed framework can be widely applied to various distributed cross domain networks and identity authentication systems.
Climate change presents intensifying environmental, economic, and social challenges, particularly for developing countries such as India, where climate vulnerability intersects with pressing developmental priorities including energy access, poverty alleviation, and sustainable urbanization. While global frameworks such as the United Nations Framework Convention on Climate Change (UNFCCC) and the Paris Agreement establish mitigation and adaptation targets, their effectiveness depends significantly on decentralized and community-driven implementation. In this context, community-based climate solutions (CBCS) have emerged as an important bridge between national policy commitments and localized climate action. This paper examines India’s renewable energy transition and electric mobility initiatives as examples of decentralized climate governance. Renewable energy programmes implemented by the Ministry of New and Renewable Energy, especially rooftop solar expansion and the PM-KUSUM scheme, promote distributed power generation, solar irrigation, and farmer-centric energy systems. These interventions contribute not only to carbon emission reduction but also to rural income diversification, agricultural resilience, and enhanced energy security. By encouraging local ownership and participatory models, such programmes integrate climate mitigation with inclusive development objectives. Complementing these initiatives, electric mobility policies advanced by the Ministry of Heavy Industries, including the PM E-Drive scheme, support the adoption of electric two-wheelers, three-wheelers, and public transport systems. These measures reduce urban air pollution, lower fossil fuel dependence, and create green employment opportunities within emerging clean energy value chains. The diffusion of electric mobility further demonstrates how local entrepreneurship, cooperatives, and community participation can accelerate low-carbon transitions. By situating these initiatives within a community-based governance framework, the study argues that decentralized renewable energy systems and electric mobility expansion reinforce climate mitigation and adaptation while promoting socio-economic empowerment. The analysis concludes that India’s evolving climate strategy reflects a gradual shift toward participatory and multi-level governance models. Strengthening institutional coordination, expanding climate finance access, and enhancing local capacity-building remain essential to sustaining and scaling community-based climate action in alignment with global climate commitments.
One of the most significant challenges encountered by electoral process is ensuring the integrity, transparency and accessibility of election systems, particularly in developing democracies where problems with trust, security and scalability remain a problem for both traditional and central electronic voting procedures. Blockchain technology has emerged as one potential solution to these challenges by providing decentralization, immutability, and cryptographic techniques, and consensus methods to analyze blockchain-based voting systems in-depth. Challenges to certain voting systems are discussed regarding their goals of voter authentication, ballot secrecy and verifiability, together done by introducing key cryptographic techniques. These techniques include digital signatures, hash functions, homomorphic encryption, and zero-knowledge proofs. Beyond technical research, the research looks at how the blockchain-based voting might be used in Bangladesh’s socio-technical and regulatory framework, paying special e
Sustainable EV charging infrastructure is fragmented by proprietary applications, vendor lock-in, and weakly time-differentiated pricing, blunting its contribution to urban-mobility decarbonisation. This paper asks whether an open-protocol, super-app-mediated photovoltaic–storage charging architecture can jointly resolve these three fragmentations under deployed field conditions and what its sustainability profile then looks like. We report a campus photovoltaic–storage microgrid integrating heterogeneous EV chargers under an open, vendor-neutral charging-control protocol with super-app authentication and payment replacing dedicated charging applications and a time-differentiated tariff aligned at the meter-interval level with the underlying utility wholesale rate; the deployment is exercised through a researcher-scheduled commissioning campaign of 13 sessions designed to establish functional correctness across the operating envelope rather than to measure user behaviour. Three results emerge across cross-vendor compatibility, onboarding friction, and grid alignment. First, basic message-level OCPP compatibility is sustained across two charger vendors under a single cloud management system—in sequential single-vendor sessions—including the full charging profile up to near-rated DC peak power. Second, the super-app-mediated workflow, which requires no charging-specific application installation and no new charger-operator account, structurally eliminates the dedicated application installation and the email/SMS/credit-card verification round-trips of conventional onboarding, compressing measured first-use end-to-end interaction to 31 s; relative to reconstructed commercial-operator baselines, this is, to the best of the authors’ knowledge, an order-of-magnitude reduction rather than a controlled benchmark. Third, mid-day energy delivery aligns incidentally with the utility off-peak window, not user-driven demand shifting, while PV-displacement and BESS-discharge contributions to charging are bracketed by scenario rather than being separately metered. The paper’s contribution is therefore a replicable, policy-embedded sustainable charging architecture validated at field scale within the New Taipei Net-Zero Carbon Demonstration Site Programme, with no claim of global novelty; the same architecture is structurally positioned to convert the observed incidental grid-friendliness into a deliberate, user-facing benefit via a hardware-free mid-day-discount redesign.
Behzad Abdolmaleki, Amir R. Asadi, Vahid R. Asadi, Stefan Köpsell · 7 authors
Stochastic Gradient Descent (SGD) is the foundation of modern machine learning (ML). In privacy-sensitive settings, gradients can reveal details about individual data points. Differential Privacy (DP) protects sensitive data during ML training by clipping gradients and adding calibrated Gaussian noise. However, existing frameworks assume semi-honest participants, which fails in adversarial or federated environments where malicious actors can bypass or alter the noise addition process, breaking privacy guarantees. We present VeriDP, a framework for verifiable differentially private training that cryptographically enforces and proves the correct execution of differentially private stochastic gradient descent (DP-SGD) in zero knowledge. VeriDP integrates Zero-Knowledge Proofs (ZKPs) with polynomial commitments, sumcheck and GKR-based proofs, and incrementally verifiable computation (IVC) to generate compact proofs of correct gradient computation, clipping, averaging, and Gaussian noise generation—without revealing private data or randomness. Unlike previous systems that only verify the final privacy budget, VeriDP enables per-iteration verifiability of each model update, providing strong privacy assurances even in adversarial settings. This establishes a novel and complete Zero-Knowledge Proof of Differentially Private Stochastic Gradient Descent (ZK-DPSGD), uniting differential privacy and verifiable computation for secure and auditable ML. Our evaluation shows that prover time increases linearly with the number of input samples, while both verifier time (2–5 ms) and proof size (3–4 KB) remain compact and effectively constant.
Demis Hassabis’s Einstein Test defines the ultimate benchmark for Artificial General Intelligence: could a system trained exclusively on pre-1911 knowledge autonomously derive General Relativity? The AI industry reads this as a scale challenge—a problem of compute and data—epitomised by Dario Amodei’s declared goal of building “a moat of the countries of geniuses in a data center.” This paper argues that this dominant Silicon Valley interpretation rests on a profound Ptolemaic assumption: that intelligence is a discrete stock that can be hoarded inside a single isolated agent. We advance a unified structural critique across three fronts. First, large-scale transformer systems are mathematically constrained to function as Stochastic Guessing Engines: thermodynamic probability samplers that intrinsically lack a semantic zero—a stable, addressable coordinate for honest epistemic absence. Without such a zero, the architecture is mechanically forced to hallucinate. Second, Tony McCaffrey’s Obscure Features Hypothesis—formalised in the McCaffrey–Spector Non-Enumerability Theorem—demonstrates that genuine novelty depends on biologically situated friction that a closed manifold cannot pre-enumerate. Third, using the Reverse Einstein Test as a continuous narrative thread, we synthesise seven independent impossibility arguments into a strict chronological cascade, culminating in the Gödel–Gauss-Bonnet proof that a sealed manifold with no puncture to reality is necessarily and irremediably incomplete. We ground our resolution in the Semiotic Web, introducing two foundational objects: the Canonical Concept Identity (CCI) and the Contextual Tokum Instance (CTI). Together they resolve the Semantic Field Equation and satisfy Yann LeCun’s four criteria for Autonomous Machine Intelligence. A key architectural consequence is the Semantic Light Cone of Care: each agent (holon) in a distributed network has a precise, mathematically bounded domain of verified knowledge and concern. This bounded self-awareness enables polycomputing across trillions of low-power edge devices—each node knowing exactly what it knows and what it does not—and allows seamless voluntary cooperation via Burgess’s Promise Theory across the platonic address space. The paper concludes by addressing Satya Nadella’s observation that “we are one sort of innovation away from the entire regime changing,” arguing that the required innovation is not a new scaling law but a notation inversion: the introduction of a semantic zero and a cryptographically verified observer’s mark. Once instantiated, the debate between AGI and Superhuman Adaptable Intelligence becomes as irrelevant as the geocentric model after Copernicus. Intelligence is not a stock inside a machine; it is a flow that reduces systemic stress through gap-closure, a property of a distributed, substrate-independent network organised in holonic federation—the Copernican Completion of Artificial Intelligence.
The rapid transformation of financial systems requires secure and intelligent architectures capable of supporting predictive analysis, decentralized operations, and collaborative knowledge exchange. Traditional banking infrastructures often depend on centralized data management, creating challenges related to privacy risks, limited interoperability, and restricted cross-entity collaboration. This research proposes a Decentralized Banking Network (DBN) designed to integrate blockchain-based distributed systems, predictive assessment mechanisms, and secure knowledge-sharing capabilities. The proposed framework enables financial institutions to collaboratively analyse data while maintaining ownership and confidentiality of sensitive information. The architecture combines distributed ledger technology, intelligent prediction models, and decentralized governance mechanisms to improve financial decision-making. Blockchain concepts provide transparency and trust among participating entities, while predictive assessment techniques support risk evaluation, fraud detection, and strategic planning. The theoretical foundation of this research is derived from distributed ledger systems, decentralized control, and federated financial intelligence. Distributed ledger technology provides mechanisms for secure and transparent transactions across independent participants (Sunyaev and Sunyaev, 2020). Recent developments in federated financial ecosystems demonstrate the potential of decentralized analytics for improving risk assessment while maintaining data sovereignty (Arifin Shawn et al., 2025). The proposed network highlights how decentralized banking models can improve security, collaboration, and predictive accuracy. However, challenges related to scalability, regulatory compliance, computational complexity, and governance remain significant considerations. This research provides a conceptual framework for future banking ecosystems where institutions can achieve secure knowledge sharing without compromising confidential financial information.