The rapid growth of urbanization in India has significantly increased the demand for efficient urban infrastructure, intelligent public services, and sustainable resource management. Cities are facing numerous challenges, including traffic congestion, rising energy consumption, water scarcity, environmental pollution, inefficient waste management, and increasing pressure on healthcare and public safety systems. Conventional urban management techniques are often inadequate for handling these complex and interconnected challenges because they rely heavily on manual monitoring and reactive decision-making. The Internet of Things (IoT), combined with smart electronic systems, has emerged as a transformative technology capable of addressing these issues by enabling real-time monitoring, automation, and intelligent decision-making. IoT-based smart electronics integrate sensors, embedded processors, wireless communication technologies, cloud computing, artificial intelligence, and data analytics to create interconnected systems that continuously collect, process, and exchange information. These technologies enable city administrators to monitor infrastructure, optimize resource utilization, improve service delivery, and enhance the quality of life for citizens. In India, the Smart Cities Mission has accelerated the adoption of IoT-enabled technologies across various sectors, including transportation, energy management, water distribution, environmental monitoring, healthcare, public safety, and digital governance. Smart electronics have enabled intelligent traffic control systems, smart street lighting, smart electricity meters, connected surveillance systems, and automated waste management solutions, thereby improving operational efficiency and reducing environmental impact. Despite significant progress, several challenges remain, including cybersecurity threats, interoperability issues, data privacy concerns, high deployment costs, and the need for standardized communication protocols. This paper presents a comprehensive discussion on the role of IoT-based smart electronics in building smart cities in India. It examines the technological architecture, key applications, implementation challenges, and future opportunities associated with IoT-driven urban development. The paper concludes that the integration of IoT with emerging technologies such as artificial intelligence, edge computing, fifth-generation (5G) communication, blockchain, and digital twin technologies will play a crucial role in achieving sustainable, resilient, and citizen-centric smart cities in India.
Feeroj Nasirkhan Pathan, Amarsingh Udhavrao Solanke, Mr. Wasim Taher Khan, Dr. Mangesh Manohar Dasare
The vision of Viksit Bharat 2047 seeks to transform India into a developed, inclusive, and globally competitive nation by the centenary of its independence. Achieving this vision requires a digitally enabled financial system that promotes innovation, expands financial inclusion, and supports sustainable economic growth. In this background, Financial Technology (FinTech) has emerged as a key driver of India's digital transformation. India's FinTech ecosystem has grown quickly with the support of Digital Public Infrastructure (DPI), including Aadhaar, Pradhan Mantri Jan Dhan Yojana (PMJDY), Unified Payments Interface (UPI), DigiLocker, India Stack and e-KYC. These initiatives have expanded access to financial services, accelerated digital payments, enhanced access to formal credit, strengthened public service delivery, and encouraged wider participation in the Indian economy. Emerging technologies such as artificial intelligence, blockchain, cloud computing, big data analytics, and application programming interfaces (APIs) have additionally enhanced the efficiency and accessibility of financial services. This chapter examines the role of FinTech in advancing the vision of Viksit Bharat 2047 by promoting financial inclusion, strengthening Digital Public Infrastructure, supporting entrepreneurship, improving governance, and fostering sustainable economic development. It also examines key challenges, that influence the long-term growth of the sector. It concludes that FinTech is more than a technological innovation; it is a strategic move of India's economic transformation.
This research introduces a novel Unified Quantum-Resilient Blockchain-Zero Knowledge Proofs Privacy Authentication Framework (QBC-ZKPAF) aimed at enhancing security in IoT environments. The system combines post-quantum cryptography, blockchain technology, and Zero Trust Architecture (ZTA) to provide secure communication, access management, and privacy-preserving authentication. It uses a Deep Q-Network Multi-Factor safe Key (DQN-MFSK) for dynamic key selection, a hybrid Reinforcement-Lattice Blockchain Key Generation for quantum-resilient key creation, and Zero-Knowledge Proofs for privacy-preserving signatures to ensure a safe Internet of Things environment. Data privacy, secrecy, auditability, traceability, and resistance to changing threats, such as quantum attacks, are all guaranteed by this architecture. Transparency and thorough post-event audit trails are supported by the blockchain ledger's immutability, which records all access attempts, data exchanges, and device interactions in an unchangeable way. Through a tracing key kept on the audit server within the Zero Trust Architecture, the architecture allows accurate source tracing in the event of suspicious activity or breaches. QBC-ZKPAF provides strong security and privacy solutions for Internet of Things networks by adopting multi-factor authentication and decentralizing identity management. The framework's efficacy is confirmed by experimental results, which show 98% privacy preservation, 700 TPS throughput, 0.98 quantum resilience, and 96% access control effectiveness, making it ideal for contemporary blockchain and IoT applications.
Xin Chen, Jun Yan, Zhiyu Yan, Jianwen Deng · 7 authors
Abstract Adapting the Segment Anything Model (SAM) to remote sensing imagery requires domain-specific updates while retaining parameter efficiency. Existing parameter-efficient fine-tuning methods usually apply a fixed adaptation capacity to all image tokens, despite the spatial heterogeneity of remote sensing scenes. We propose Token-Adaptive LoRA, which integrates rank-differentiated LoRA experts with a Noisy Top-1 router. For each token, the router selects one expert, allowing adaptation capacity to vary across tokens while the pretrained SAM encoder weights remain frozen. We evaluate the method on TGRS-HRRSD object detection and LoveDA semantic segmentation using SAM-based downstream architectures. On TGRS-HRRSD, Token-Adaptive LoRA achieved 85.3% mAP@0.5, improving rank-8 LoRA by 0.4 percentage points and ConvLoRA by 0.3 percentage points. The method introduced 460.82K trainable adaptation parameters and increased computation by 0.15% relative to the baseline. On LoveDA, it achieved 53.46% mIoU and 66.16% mAcc, exceeding LoRA by 0.37 and 1.44 percentage points, respectively. These results show that token-wise routing among rank-differentiated experts can improve SAM adaptation across detection and segmentation tasks with limited additional computation.
The χ‑spectral framework developed in this work establishes a unified operator‑geometric foundation for physical law, integrating quantum measurement, modular state reduction, spectral geometry, and gravitational curvature into a single mathematically coherent structure. Physical measurement is formulated as an intrinsic operator‑spectral transition generated by the bounded self‑adjoint observable M_chi(k) = Phi_chi(k) + B_chi(k) + R_chi(k), which combines phase geometry, boundary tension, and χ‑spectral curvature into a non‑singular measurement mechanism. Probability amplitudes P_n(k) = |_chi|^2 are derived directly from the χ‑inner product, demonstrating that Born’s rule emerges from arithmetic geometry rather than axiomatic postulates. A central result of the χ‑spectral framework is the rigorous proof of compatibility between ZEBTS‑SUPER gravitational dynamics and quantum mechanics. Gravitational curvature R_chi(k) enters the measurement operator M_chi(k) as a bounded geometric observable, ensuring ultraviolet stability, finite expectation values, and strict unitarity across all scale layers. Collapse dynamics are formulated as bounded modular projections, guaranteeing non‑perturbative, divergence‑free state reduction. Decoherence is shown to be a structural spectral gradient D_chi(k) = M_chi(k+1) – M_chi(k), providing a deterministic geometric mechanism for coherence loss without environmental reservoirs. The scale‑layer commutator C_chi(k) = [M_chi(k+1), M_chi(k)] encodes contextuality and order‑dependence as structural consequences of χ‑operator geometry. Together, these results demonstrate that quantum dynamics, gravitational curvature, measurement theory, and modular collapse are fully compatible and mutually reinforcing within the χ‑spectral operator framework. The theory achieves conceptual and mathematical closure: all physical observables remain bounded, all transitions remain unitary, and quantum–gravitational consistency is established as a direct consequence of χ‑spectral geometry.
Transparency in public affairs interactions between companies and governments is critical to democratic legitimacy, yet existing lobby registers suffer from fragmented reporting, weak record integrity, limited traceability, and compliance gaps. This paper reports a Design Science Research (DSR) study that develops and evaluates a permissioned blockchain architecture for mandatory Public Affairs transparency. Two stakeholder surveys provided empirical grounding: Survey 1 (N = 61 domain professionals) elicited functional, non-functional, and GDPR compliance requirements, while Survey 2 (N = 14 practitioner evaluators) assessed a proof-of-concept implementation on Hyperledger Fabric following a live demonstration. Findings reveal widespread concerns over non-repudiation and auditability in current systems — 87% rated existing record integrity as weak—alongside strong endorsement for blockchain’s immutability, versioned audit trails, and hybrid on-/off-chain design to ensure GDPR-aligned traceability. Post-demonstration evaluation achieved a mean score of 4.6/5 for traceability and integrity, and 86% of evaluators recommended real-world piloting. The study makes three contributions: (i) an empirically derived requirements model and information-lifecycle framework; (ii) a hybrid permissioned-blockchain blueprint implemented on Hyperledger Fabric; and (iii) a replicable stakeholder-centric DSR methodology for sociotechnical artefact design in regulated governance contexts.
Tendermint is among the most widely studied and deployed Byzantine fault-tolerant (BFT) consensus protocols, owing in part to its native leader-rotation mechanism that subsumes complex view changes. Like most partially-synchronous BFT protocols, Tendermint tolerates $f 5f$ setting that decides in two communication steps in the good case, while preserving Tendermint's leader-rotation structure. Fast Tendermint collapses Tendermint's prevote and precommit steps into a single voting step and merges the $locked$ and $valid$ state. We give proofs of agreement, validity, and termination, and a formal specification in Quint, a modern surface syntax for TLA+, used to model-check the protocol.
Zeta Avarikioti, Dimitris Karakostas, Karl Kreder, Shreekara Shastry
Our work presents a defense mechanism against Maximal Extractable Value (MEV) opportunities in distributed ledgers. The mechanism relies on the idea of enforcing a verifiable delay when generating transactions, such that a block creator cannot react to the appearance of a MEV opportunity without breaking liveness. We present positive results both in the Byzantine setting and in a game theoretic model of rational participants. We additionally present negative bounds that outline the limitations of this line of defense. Finally, we explore real-world implementation details of verifiable delays and show that, based on historical MEV data, our mechanism could realistically help prevent most existing MEV threats.
Sofia Bobadilla, Humaira Afrin, Angela Novelli, Martin Monperrus
Blockchains are among the most adversarial environments in computing. Billions are stolen by cybercriminals who exploit vulnerabilities. This is an open problem and no concept or technique has proven to really make a difference. In this paper, we claim that the classical notion of program invariant is perhaps the most powerful solution to the problem. We devise anoriginal experimental protocol to 1) study how invariants would have protected against past real-world attacks and 2) whether state-of-the-art automated tools can find them. The experimental toolchain is sophisticated. It is based on INVARIANTEVAL, a benchmark of 28 real Ethereum exploits, each paired with a human-authored invariant that blocks the attack. We validate every invariant with PONDEREPLAY, a replay framework that re-executes transactions in order to prove the correctness and soundness of smart contract invariants. We demonstrate that smart contract invariants block all the cybercriminal attacks in INVARIANTEVAL, fully validated by replaying 108,637 historical transactions. Our large-scale experiments clearly demonstrate that smart contract invariants protect against cybercriminals.
Public blockchain data enables large-scale DeFi-related analysis, but many existing approaches are application-specific, difficult to scale, or hard to interpret. This research proposes a scalable, application-agnostic framework for \emph{persistent behavioural pattern discovery} from large-scale blockchain activity. It constructs behaviour sentences enriched with contract, token and market context, then applies a two-step embedding process: sentence-level embeddings capture individual actions, while sequence-level embeddings capture user behaviour over time. An interpretable behavioural profiler characterizes discovered communities through behavioural motifs, routines, temporal dynamics, entity exposure, and suspiciousness evidence. Evaluation on Ethereum using over 30 million transactions shows that the framework uncovers both routine and malicious behavioural patterns, including decentralised exchange (DEX) trading, NFT activity, phishing, bot operations, oracle manipulation, and rug-pull schemes. Importantly, many patterns remain stable across independent observation windows, enabling the identification of long-term behaviours beyond a single analysis period. The proposed framework combines scalability, interpretability, and persistence analysis, supporting blockchain forensic investigation, behavioural attribution, and threat discovery.
Quantum Cellular Theory of Space: A Testable Cosmological Model of a Dividing Causal Network Author: Martin JámborState of knowledge captured as of: 9 August 2026 Quantum Cellular Theory of Space is a research hypothesis in which space is not a fundamental continuous stage but the macroscopic manifestation of a discrete local network. In this picture, observed spacetime, matter, and fields would be emergent descriptions of the collective behaviour of its cells. The theory asks whether one physical substrate can explain the common origin of cosmic expansion, accelerated expansion, the formation of matter, an unseen clustering component, a relativistic relic, the propagation of light, and physical irreversibility. This is not a biological model. The terms cell, fuel, ash, steam, and scar denote distinct roles in the energy and state description of the network. The hypothesis is not yet an experimentally confirmed replacement for general relativity, quantum field theory, the Standard Model, or standard cosmology. In domains where those theories are validated, it must reproduce their successful laws and observational bounds. Its contribution would lie in deriving their common microscopic origin or predicting a new measurable deviation. Physical picture The basic working idea is that cells of space can locally rearrange or divide. Macroscopic expansion would then be not motion into an external void but a change in the number and arrangement of the degrees of freedom from which space emerges. The energy component that enables rearrangement is called fuel. In the effective cosmological description it has pressure close to vacuum pressure, and it can therefore carry part of the physical role attributed to dark energy and accelerated expansion. Energy and momentum must remain conserved when fuel is processed. The model investigates three possible output channels: matter as stable or long-lived excitations; ash as a nonrelativistic gravitationally clustering residue that may take over part of the role of dark matter; steam as a relativistic or freely propagating share of the energy that may leave an imprint in the early radiation or thermal background. It has not yet been determined which channels actually exist, what their fractions are, or whether they arise in parallel, sequentially, or through mixed branching. The answer must come from a common local law and observations, not from a verbal choice of mechanism. A scar is a candidate persistent change in the internal state of a cell or its links after a physical event. It is intended to carry local memory and may provide a basis for the arrow of time. It has not yet been shown whether the same mechanism can also explain a single outcome of a quantum measurement and the Born rule. Light is investigated as a wave or excitation of the common substrate. If light, matter, clocks, and measuring rods are all realizations of the same network and share one local light cone, all inertial observers may measure the same limiting c. This objective still requires derivation of the photon sector, a common metric, boost symmetry, absence of impermissible birefringence, and the equivalence principle. Central mathematical bridge The global mean-field effective overhead of rearrangement is written as delta = 1 / (<k> + C) where <k> is the mean number of face neighbours in the reference Poisson–Delaunay network and C is the working internal capacity of a cell. For <k> = 48 pi^2 / 35 + 2 ≈ 15.535 C = 28 this gives delta ≈ 0.02297 This overhead is connected to the effective equation of state of fuel: p_f = (-1 + delta) rho_f w_f = p_f / rho_f = -1 + delta The fluid form is the same as in modern cosmology; what differs is the proposed origin of w_f+1 in the geometry and capacity of the network. The value C=28 is read as the number of bosonic states in the restored phase of the Standard Model, but this identification does not yet have an independent microscopic derivation. The arithmetic 16_gluon + 8_EW + 4_Higgs = 28 counts the four real Higgs directions as already including the three directions that become Goldstone modes; it does not add them a second time. It remains open why cell capacity should count precisely bosonic and not fermionic degrees of freedom. Because the value 28 was chosen before this link was fully derived, its success in downstream calculations is not independent confirmation of the theory. If the local degree of the network varies, the overhead of one cell would have the form 1/(k+C) and its average would be <1/(k+C)>. Jensen's inequality then gives <1/(k+C)> >= 1/(<k>+C) with a strict inequality when the degree has nonzero variance. Without the distribution P(k), the value 0.02297 is therefore the mean-field value and a lower bound for this locally averaged branch, not a calculated local overhead. Cosmological background For x=ln a, the effective homogeneous model uses the densities of fuel rho_f, ash rho_c, baryons rho_b, and radiation rho_r: d rho_f/dx = -3 delta rho_f - lambda (H0/H) rho_f d rho_c/dx = -3 rho_c + lambda (H0/H) rho_f d rho_b/dx = -3 rho_b d rho_r/dx = -4 rho_r H^2 = (8 pi G / 3) rho_total Transfer between fuel and ash has opposite sources in the homogeneous description: Q_f = -Q_c = -lambda H0 rho_f The total background energy ledger is therefore conserved. lambda describes a family of effective transfer rates, not a derived constant of nature. The calculations use the data-calibrated reference point lambda=0.15; it is neither an independent prediction nor the only allowed value. The separately examined points 0.10 and 0.15 do not establish that the whole interval between them is allowed. A continuous physically admissible range must still pass stability, the null limit, and a joint comparison with BBN, CMB, BAO, structure growth, and lensing. Data used to select or normalize the reference point cannot be counted again as its independent confirmation. One homogeneous universe must have one expansion history H(a), independent of the Fourier mode later used to describe a perturbation. The early dimensionless perturbation coordinate z = k a / [H0 sqrt(Omega_r0)] must therefore not enter the background as a physical global scale. For p=4-3 delta, the mode amplitude is written as Phi(k) = A_f [H0 sqrt(Omega_r0) / k]^p which yields the homogeneous fuel term Phi(k) z^p = A_f a^p For the inputs used here, A_f=7809.270101963506. This is a conditional normalization of the specified background, not a new universal constant or a separate fit to observations. Linear perturbations and stability In a simplified nine-variable model with effective perfect radiation, the complete three-mode regular basis, kinetic and gradient signs, characteristic speeds, null limit, static Einstein constraints, behaviour at q={30,300,1000}, and numerical convergence were tested. No forbidden high-frequency growing instability was found within this scope. The result applies only to the stated model. It is not a microscopic no-ghost theorem, a proof of global hyperbolicity, or a complete evolution of photons, neutrinos, baryons, fuel, and ash. Static Einstein constraints alone do not prove their dynamical Bianchi propagation. The scalar cosine-Laplacian operator is exactly even in wave number, so its expansion contains no odd linear term. This property is necessary for a viable discrete scalar sector, but it does not by itself derive full Lorentz invariance, photon dispersion, or the equivalence principle. Quantitative consequences and viability conditions The following values are commitments of the specifically stated formulations. Agreement keeps them viable but does not confirm the cellular mechanism. A robust disagreement can exclude them only after a complete link between the model and the measured quantity, including uncertainties, covariances, and systematics. Quantity or phenomenon Value or physical condition Limit of interpretation extra relativistic relic Delta N_eff=0.0535, hence N_eff≈3.10 Applies to an early-decoupled two-polarisation thermal formulation; the local source, branching, exit, and reheating are not derived. scalar tilt n_s=0.9656 +/- 0.0016 Target of the exact delta/m=1/2 mechanism; the width is neither a new posterior nor an uncertainty derived from the formula. tensor-to-scalar ratio sharp target r<1e-10; broader practical marker r>=1e-3 The complete tensor operator, source, normalization, and B-mode observable map are missing. Hubble constant H0≈66.4 +/- 0.4 km/s/Mpc Condition of the frozen background, not a new global fit or a solution to the Hubble tension. clustering S8≈0.86–0.87 Condition of the simplified growth formulation, not a full Einstein–Boltzmann result. effective CPL description w0=-0.919, wa=-0.612 Joint target of the accounting reconstruction; it is not a microphysical equation of state for fuel. sterile ash no confirmed nongravitational signal A numerical experimental window can be defined only after deriving the mass, spin, abundance, lifetime, and couplings of ash. exact n_s-w relation no active claim The exact formula is not part of the current theory. time drift of delta delta=0.02297 is only a constant benchmark The function delta(a) or delta(x) and a measurable drift window have not been derived. scalar dispersion the odd linear coefficient is exactly zero The result applies only to the stated scalar operator. thermal steam or wave background T≈0.905 K, peak near 53 GHz This is the same thermal commitment as Delta N_eff; identification of the relic with gravitons has not been derived. The thermal result uses the standard entropy arithmetic for an early-decoupled bosonic relic: Delta N_eff = (4/7) g_x [10.75/g_*s,dec]^(4/3) with g_x=2 and g_*s,dec=106.75. The cellular hypothesis adds a possible causal origin of steam in the processing of vacuum fuel, but it does not yet determine what fraction of energy enters this channel or how the relic survives unt
W. C. Yang, J. F. Qiao, J. F. Hu, Jie Wang · 5 authors
This study presents a multi-level verification system for secure communication protocols in energy billing infrastructures. The proposed framework integrates device attestation, network integrity verification, privacy-preserving aggregation, billing validation, and immutable auditing to address security vulnerabilities across Advanced Metering Infrastructure (AMI) communication chains. A Hybrid Secure-Efficient Protocol (HSEP) combining elliptic curve cryptography, homomorphic encryption, and zero-knowledge proofs is developed to provide secure authentication, privacy protection, and verifiable data integrity while maintaining low computational overhead. Experimental evaluation using a large-scale AMI testbed demonstrates that the proposed system significantly improves tampering detection capability, achieving an intrusion detection AUC of 0.94 while maintaining an average energy consumption of 1.55 J per transaction and acceptable communication latency for large-scale deployment. The architecture exhibits strong scalability, robustness, and rapid dispute-resolution performance under multiple attack scenarios. The proposed framework is particularly applicable to wireless smart metering networks and antenna-enabled AMI communication infrastructures, where reliable data transmission, secure protocol verification, and resilience against communication-layer attacks are essential for trustworthy energy billing and grid operation. This work provides an effective engineering solution for secure, privacy-preserving, and verifiable communication in modern intelligent energy systems.
The rapid development of cryptocurrencies, stablecoins, and central bank digital currencies (CBDCs) has transformed the global monetary landscape and accelerated the transition toward a cashless society. While critics argue that digital currencies threaten financial stability due to volatility, disintermediation, energy consumption, and regulatory concerns, this paper contends that the increasing competition among digital and fiat currencies can generate significant economic benefits. By examining the evolution of cryptocurrencies, the emergence of stablecoins, the global adoption of CBDCs, and the case of Zimbabwe's hyperinflation, this study argues that currency competition encourages governments to pursue more disciplined fiscal and monetary policies, strengthens policy credibility, and helps anchor inflation expectations. Greater monetary credibility also expands policymakers' ability to respond effectively to future economic downturns. Although digital currencies present important risks, many of these challenges can be mitigated through technological innovation, appropriate regulation, and institutional development. Overall, this paper concludes that a wellmanaged transition toward a cashless society can promote competition, innovation, and long-term economic resilience rather than undermine financial stability.
This paper presents a verified funder landscape and fit-score shortlist for sustaining QNFO, a two-year-old, solo-run, AI-assisted research platform that has produced an open corpus of approximately 1,000 method papers across seven program areas. Every funder fact was verified by live HTTP retrieval on 2026-08-13 across twenty-six pages spanning Web3 and IPFS ecosystem grantors, open-science philanthropy, and decentralized-science programs; anything not verified live is explicitly flagged. The analysis scores eleven funders on eligibility for an unaffiliated individual, topical fit with decentralized and epistemics-oriented research, and application friction, yielding a weighted ranking led by NLnet NGI Zero (calls open September 3, 2026; deadline November 3, 2026, 12:00 CEST) and Emergent Ventures, followed by the Foresight Institute, Filecoin Foundation, the Ethereum Ecosystem Support Program, Gitcoin, and the Effective Altruism funds. A sequencing calendar spans August 2026 through 2027, including the Sovereign Tech Agency Fellowship cycle. The paper documents application-readiness gaps (legal entity, residency, tax position, public identity), per-funder pitch skeletons, and framing cautions, including the risk of presenting corpus volume as rigor. It closes with an agent-executable action plan.
Hypothesis. Among 20 confirmatory genealogical axis units (116 languages), pronunciation forms of three segments recur identically across at least three genealogically independent units less often than each unit's own phonotactics predicts: obs/E < 1.0 at form length 3. The direction is specified in advance; a ratio above 1.0 disconfirms the hypothesis rather than supporting it. Design. Confirmatory replication of a count. Forms are normalised to CLTS/BIPA, filtered by a grammatical-word exclusion, and grouped into clusters of identical segment sequences. A cluster counts when attested in at least 3 axis units and 3 languages. The observed number of length-3 clusters is compared with the expectation under a per-language positional bigram null refit on the same filtered corpus, reported with two uncertainty sources that are never pooled: Monte Carlo over 1000 null replicates, and a bootstrap over the 20 axis units. The confirmatory arm has not been analysed. The registered quantity has never been computed for any confirmatory unit. The blind is verified, not asserted: urortkontroll.py, included here, checks four independent traces and reports one stated limitation rather than claiming absolute untouchedness. The decision rule was fixed in advance and is cryptographically timestamped: if the 95% interval from either uncertainty source covers 1.0, the result does not stand. That record is anchored in Bitcoin block 960700. Identity relation, null model and adequacy bands were each fixed in a decision record committed before the measurement it governs. Resource type: Zenodo's vocabulary contains no 'preregistration' type. 'Preprint' is the nearest available and is used for that reason alone. Not included: the corpus, the population files, and the exploratory/confirmatory split assignment — publishing the assignment would reveal the confirmatory half.
When we describe a complicated system by a few coarse measurements, we face one recurring question: are the readings we have now enough to say what it will do next? Sometimes yes; sometimes they look complete but are not, and only pushing the system reveals it. This report turns that question into a checkable procedure. Five inexpensive probes first screen the data — description cost, identifiability, memory duration, change across scale, topological shape — no single probe deciding. We then ask, in order: does the present coarse state beat knowing nothing, and, once known, does history add more. Asking the first matters — history that “no longer helps” can mean the state suffices or that the future is unpredictable, and only the total separates these. Later stages ask whether look-alikes respond differently when pushed. The procedure reports a bottleneck and whether a layer has formed. We calibrate on known-answer cases: a classical system computed end to end (a closed layer, a history-limited case, a case separable only by intervention, and an unpredictable control a naive rule would misread as closed); a charge-to-particle stress test that stops short; and a genuine two-qubit process whose branches are passively identical yet separated by one intervention. We then run real series — carbon dioxide, sunspots, river flow, and equity-index and Bitcoin prices — where next-day returns read as no detected signal while volatility clusters, consistent with what is independently known. Every “no signal” is resource-relative: stamped with the resource R used. The procedure settles only the two ends — a closed layer, or no detected signal — and refuses the process path between; it classifies rather than inventing the next layer’s laws.
Although stablecoins occupy a segment of digital-asset markets in which price stability is central by design, their temporary departures from reference values may reveal important information about latent risk and market stress. In this paper, we examine whether bubble and crash signals extracted from traditional cryptocurrencies and stablecoins improve volatility, Value-at-Risk, and Expected Shortfall forecasting and, in connection with these forecasting gains, contribute to the assessment of cross-asset contagions. The analysis applies the Bubble Crash–GARCH models, in which extreme price phases are identified through the Phillips, Shi, and Yu real-time monitoring procedure and incorporated into the conditional mean of returns through event-based dummy variables. For stablecoins, extreme episodes are not inferred from price dynamics in isolation but from deviations between the observed price and the asset-specific reference value. The empirical investigation focuses on Bitcoin, Ethereum, Tether’s USD-pegged (USDT), and Tether Gold and evaluates asset-specific bubble–crash effects and bidirectional contagion channels between traditional cryptocurrencies and stablecoins, using Bitcoin and Tether as the leading representatives of the two market segments. The findings indicate that accounting for bubble and crash episodes leads to more accurate volatility forecasts than standard GARCH benchmarks. For Value-at-Risk and Expected Shortfall, the bubble–crash specifications can improve tail risk forecasting at several tail probability levels through more accurate coverage, lower quantile loss, and stronger ESR backtesting performance. The results also reveal different degrees of price exuberance across the two asset categories: while extreme price dynamics are more evident among traditional cryptocurrencies, deviations from fundamentals are rare for stablecoins. Among stablecoins, USDT exhibits limited but detectable exuberance, whereas Tether Gold does not display extreme price episodes. However, when such deviations occur, as in the case of USDT, they generate significant contagion effects on major cryptocurrencies. Notably, extreme episodes originating in USDT have a stronger impacts on Bitcoin and Ethereum than the reverse spillovers from traditional cryptocurrencies to USDT. Overall, the evidence suggests that stablecoins are not merely passive instruments within the digital-asset ecosystem. Even temporary deviations from their reference values contain valuable information for risk forecasting and contagion monitoring.
# Provider Description Microscopic changes in cells and connections can later contribute to a distributed memory, perception, or imagined scene. This paper asks how relations encoded at one physical scale can constrain patterns at another scale without requiring the brain to enlarge a microscopic trace into a literal copy. It separates dendritic morphology, network topology, temporal dynamics, and functional reinstatement, then asks whether finite-range scaling measurements add predictive or causal information beyond ordinary morphology, topology, activity history, oscillatory variables, single-scale models, and flexible nonlinear alternatives. The paper develops the historical Self-Aware Networks proposal called FRACTAL Conscious Perception as a testable cross-scale transformation rather than a claim that the brain is one ideal mathematical fractal. Four generations of synthetic applications test estimators, graph and temporal representations, capacity differences, route erasure, invertible transformations, exact matched restoration, nonspecific restoration, no-route controls, decoy shifts, and simpler single-scale alternatives. The record is deliberately mixed. Earlier systems contain favorable planted results, reversals, nulls, failed compensation, and a recovery statistic that could reward destructive collapse. A later frozen route-identification system passes all ten declared transformation, erasure, restoration, and refusal gates while still allowing raw ridge to perform slightly better and the correct single-scale model to win decisively when only one scale carries the target. The release includes the manuscript, six figures, frozen contracts, source and claim ledgers, raw and summary outputs, deterministic replays, tests, formal-verification receipts, and exact hashes. Seventeen Lean theorems establish bounded algebraic, rotation, and route-erasure invariants. They do not establish a biological neural mechanism or conscious experience. The applications use disclosed synthetic generators and do not constitute neural recordings, clinical evidence, or therapeutic guidance. The future biological evaluation remains sealed and unopened. ## Keywords fractal neuroscience; dendritic morphology; neural reinstatement; finite-range scaling; route identification; memory; connectome; multifractal dynamics; Self-Aware Networks; reproducibility
This paper asks what must be added to three-dimensional semantic segmentation before a distributed biological system can be said to organize differentiated, object-specific content. It begins with ordinary object perception and separates class labels, instance identity, border ownership, recurrent completion, multisensory registration, receiver state, Phase Wave Differentials, action, and returned sensory correction. The paper introduces a fifty-equation formal specification and an Object-Boundary Registration Benchmark. A deterministic reference application, fitted synthetic pilots, distribution-shift tests, latent and global alternatives, targeted ablations, calibration analysis, six evidence figures, and a machine-checked finite contract kernel make the proposal auditable. The synthetic results are mixed: typed receiver structure outperforms a global summary, while stronger latent alternatives match or exceed it under some noise and missingness conditions. Those adverse results remain central to the paper. The work therefore presents a testable research program, not completed biological or consciousness validation. A staged biological protocol is frozen, but it has not been run and the final test remains sealed. The public companion archive contains the complete cumulative manuscripts, source and claim ledgers, executable application, tests, structured results, negative-result record, figure provenance, formal proof receipts, and reproducibility instructions.
Open access
2 source records
Cell Image Analysis Techniques
Face Recognition and Perception
Generative Adversarial Networks and Image Synthesis
The Prop Trust Verified Standard (PTVS) v1.0 Reference Architecture establishes the definitive technical specification, capability matrix, and implementation guidelines for the physical verification of tokenized Real-World Assets (RWAs) within the European regulatory framework. This document resolves the "Physical Oracle Gap" — the structural inability of Distributed Ledger Technology (DLT) systems to attest to the physical existence, structural integrity, and legal encumbrances of off-chain assets backing tokenized securities — through a deterministic four-pillar architecture: Pillar I — eIDAS 2.0 Qualified Forensic Audits: On-site inspections conducted by sworn judicial experts under Qualified Electronic Signatures (QES) per Regulation (EU) 2024/1183. Pillar II — SHA-256 Cryptographic Lineage: Canonical JSON serialization with deterministic hashing anchored in permanent registries. Pillar III — Smart Contract Circuit Breakers: The open-source PTVSClaimInjector.sol contract (MIT License) enforces automated protective actions based on PTVS Score. Pillar IV — PTCE Network: Decentralized network of Prop Trust Certified Experts with 85/15 revenue split. Institutional validation: Formal submissions to ESMA (FOI/ESMA/2026-001), EBA (FOI/EBA/2026-002), EIOPA (FOI/EIOPA/2026-003, confirmed & registered), and ECB/SSM (FOI/ECB-SSM/2026-004, ADITO portal) Application to INATBA RWA Working Group (FOI/INATBA/2026-005) Permanent registration at CERN/Zenodo, HAL/CNRS (hal-05713062v1), OSF (DOI: 10.17605/OSF.IO/7D2SJ), and U.S. Copyright Office (Cases 1-15210573311 & 1-15234961091) Open governance via the PTVS Technical Board (17 seats, W3C/ISO-inspired) Document scope: 17 pages covering architecture overview, PTVS Score methodology (0-100), Verifiable Claims lifecycle, ERC-3643/T-REX integration, regulatory alignment matrix (MiCA, Solvency II, Eurosystem, eIDAS 2.0), governance model, 20-capability prior art inventory, and comparative analysis vs. Chainlink, Proof of Reserve, IoT sensors, Big Four audits, and registry oracles. Lead Researcher: Aurelio Tamarit Blay, Certified Judicial Expert (Exp. No. 0161, Spain), ORCID: 0009-0007-5824-3602, Wikidata: Q140774713. Institutional motto: Veritas in Re · Certitudo in Code Canonical source: https://forensics-oracle.org/reference-architecture/
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Blockchain Technology Applications and Security
Digital and Cyber Forensics
Physical Unclonable Functions (PUFs) and Hardware Security
Paper 14 gives an analytical model of the Qoin economy as a dynamic network: node balances that rise and fall with local creation and consumption events, a physical de- livery graph those events populate, and closed-form results for adoption, topology, and resilience under stated assumptions. Those results are the model’s skeleton. This pa- per is discursive rather than mathematical: it asks what would actually need to be built to give that skeleton stochastic life, test its assumptions, and check its closed-form predictions against simulated behaviour — before any of it touches a real deployment. Five requirements follow directly from Paper 14’s own structure, not from any new modelling choice. The event log is not an implementation detail but the correct primary data structure, because Paper 14 already defines node balance as a derived quantity rather than stored state — the model specifies event sourcing whether or not the word is used. The simulation engine should be discrete-event rather than continuous, because every quantity in the model changes at a point in time, not continuously. Node arrival, edge formation, and lifecycle-window realisation are three distinct stochastic processes, each with its own calibration target, and should not be collapsed into one undifferentiated source of randomness. Calibrating the model against reality requires specific, nameable data that does not yet exist, and the paper says exactly what that data would need to be. And nothing built should be trusted beyond what Paper 14 already proves analytically until it reproduces those proofs first. This paper does not specify the real distributed ledger of Paper 1, does not perform any calibration (no pilot data exists), and does not address deployment, production, or user-facing engineering. It specifies a research instrument for studying the dynamics, nothing more.
Papers 12 and 13 establish, in prose, that the Qoin economy grows through voluntary adoption driven by a structural incentive (the double remuneration asymmetry) and a self-reinforcing network effect, and that its distributed ledger architecture protects it from institutional destruction. Both claims are narrative. Neither is modelled. This paper treats the Qoin economy as what it already is beneath the ledger’s bookkeep- ing: agents with a local Qoin balance that rises on wealth creation and falls on wealth consumption, connected by a dynamic graph recording the physical delivery of wealth between them — not a payment network in which Qoin itself moves along edges, but closer to a reaction network, in which local state changes are triggered by relationships the graph records. Node arrival is the boundary event of Paper 12; edge arrival is each completed delivery. Three results follow. First, the qualitative adoption story of Papers 12–13 is a Bass diffusion process: an ordinary differential equation with a derivable S-curve, an inflec- tion point, and two coefficients — one tied to the unconditional attribution advantage available to currently unmonetised creators, the other to the compounding profile ad- vantage of existing participants. Second, profile-based selection (Paper 3, Paper 4) is a preferential-attachment mechanism, and preferential attachment produces heavy-tailed, plausibly scale-free degree distributions — which carries a specific, testable consequence: such networks are robust to random node loss but fragile to targeted removal of high- degree hubs. This bears directly and unfavourably on the claim, made in Paper 13, that the ledger’s technical decentralisation protects the Qoin economy from institutional at- tack: the ledger and the delivery network built on top of it are different graphs, and only one of them has been shown to be attack-resistant. Third, Paper 6’s community-bounded federation is, in network terms, a modularity-preserving design choice, and modularity is precisely the structural property that bounds the damage a targeted attack on one community can do to the others. This paper is analytical throughout: closed-form and asymptotic results, not simulation or empirical calibration against real Marketplace data. That is deliberately left as the next piece of work.