This study examined blockchain technology's potential to enhance audit efficiency in selected service firms. Traditional auditing is often hindered by data manipulation, limited transparency, time-consuming verification, and high costs challenges that blockchain's decentralised, immutable, and transparent ledger system can plausibly address. The research assessed blockchain's role in improving audit efficiency, focusing on automation and realtime auditing, distributed ledger effects, and consensus mechanisms. Data was gathered through questionnaires, observation, and a technical readiness survey, and analysed using descriptive statistics, inferential statistics, and multiple regression. The study evaluated current auditing practices to identify the benefits and barriers of blockchain implementation, examining existing audit challenges, blockchain's capacity to resolve them, and the implications for service firms. Respondents were drawn from service firms with interest or prospects in adopting blockchain for audit activities. Findings showed marked improvements in audit accuracy, transparency, and overall efficiency, though adoption barriers, cost, and the need for regulatory structures were also identified. The study contributes to the growing body of knowledge on blockchain's practical application in auditing, offering guidance to service firms, audit practitioners, and policymakers on successful implementation. By addressing these challenges and leveraging blockchain's opportunities, service firms can achieve cleaner, safer, and more efficient audit practices. The research confirms that blockchain technology plays a significant role in enhancing audit efficiency within service firms.
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Blockchain Technology Applications and Security
Innovations and Analysis in Business and Education
Ensuring transparency and traceability in horticultural supply chains is difficult due to complex logistics, seasonal variability, and multiple intermediaries.We propose a framework that couples b-local irregular vertex coloring (b-LIVC) with a blockchain architecture to enable end-to-end verification of production and trade.On the Jember Regency subdistrict graph, we compute the b-local irregular chromatic number and obtain Ļ b-lis (J) = 6, yielding six planting color classes that schedule sowing and harvests to distribute output across the year.The local irregularity induces distinct neighborhood weights, which we use as cryptographic features for unique, verifiable batch identifiers.We implement the pipeline on a public blockchain: harvest lots are tokenized as video NFTs with QR links to a verification page and on-chain records.The integration of discrete mathematics and distributed ledgers provides auditable provenance and transaction history, practical scheduling that reduces harvest clustering, and a low-overhead mechanism for farmer-level transparency.
Let $\xi(s)=\frac12 s(s-1)\pi^{-s/2}\Gamma(s/2)\zeta(s)$ be the completed Riemann xi-function, and let $F(x)=\frac{\xi'}{\xi}\!\left(\frac{1}{1-x}\right)=\sum_{n\ge 0} f_nx^n$ initially denote its germ at the origin. We introduce the real symmetric Toeplitz--Hankel matrix $c_{ij}=f_{|i-j|}-f_{i+j+1}+\delta_{ij}f_0, \qquad i,j\ge 0.$ We prove that the Riemann hypothesis is equivalent to positive semidefiniteness of every finite leading principal block of this matrix. More strongly, the full matrix condition is equivalent, for the purpose of testing the Riemann hypothesis, to only the adjacent local inequalities $2f_0-f_{2n+1}\ge 0,$ $(2f_0-f_{2n+1})(2f_0-f_{2n+3})\ge (f_1-f_{2n+2})^2 \qquad(n\ge 0).$ The converse implication uses a Pringsheim bootstrap: these local inequalities force the germ of $F$ to have Taylor radius at least one, hence exclude zeros of $\xi$ from the half-plane $\Re s>1/2$. If $\lambda_n$ are the Keiper--Li coefficients, then $f_n=\lambda_{n+1}-2\lambda_n+\lambda_{n-1}$, so the criterion is a local quadratic condition on their second finite differences. This is an equivalent reformulation, not a proof of the Riemann hypothesis. To the best of our knowledge, the exact Toeplitz--Hankel matrix and its reduction to adjacent $2\times2$ conditions have not appeared previously.
Recallspection is a neuro-symbolic architecture that decouples semantic representation from factual retrieval, achieving Exact Memory Recall (EMR = 1.0000) and bounded drift (Ī² < 1e-11) across 51+ dependent reasoning steps. Key Innovation: Replaces approximate nearest-neighbor search with O(1) deterministic hash routing and k-quorum verification, eliminating the catastrophic coherence degradation that plagues Large Language Models in multi-hop reasoning tasks. Proof Included: Reproducible test demonstrating 51/51 hop completion with zero algorithmic drift (measured drift: 1.27e-12, attributable solely to IEEE 754 float64 precision limits). Core Mechanisms: - Semantic Geometry: Entities as normalized vectors in ā^d, relationships as displacement vectors- O(1) Deterministic Routing: SHA3-256 hashed overlapping slots with ephemeral salt rotation- Quorum Verification: k-slot majority voting (default k=4, quorum=3)- Self-Healing Audit: Cryptographic logging with automatic corruption detection and repair License: GNU AGPLv3 (ensures network-level copyleft and prevents proprietary enclosure) Repository: https://github.com/gnowingtheafterthought-crypto/recallspection Live Demo: https://recallspection.onrender.com
This paper assesses the adequacy of technology-neutral privacy frameworks in addressing quantum threats to zero-knowledge proofs (ZKPs) and other privacy-enhancing technologies (PETs) in global data protection regimes. Challenging assumptions that cryptographic innovation inherently bolsters privacy rights, the analysis demonstrates how post-quantum migration, absent binding regulatory duties, risks entrenching a āquantum divideā in access and liability. Grounded in legal frameworks and actual deployments, including Zcashās classical Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (ZK-SNARKs) and NantHealth Inc.ās quantum-aware homomorphic encryption systems, the paper contends that access to PETs is becoming ever more determined by institutional capability and geopolitical factors, as illustrated by comparative case studies. This research evaluates the efficacy of statutes such as the European Unionās (EU) General Data Protection Regulation (GDPR) (Article 32), the California Consumer Privacy Act (CCPA) (Ā§ 1798.150), and the Health Insurance Portability and Accountability Act (HIPAA) (45 C.F.R. Ā§ 164.308) in imposing liability for quantum vulnerable systems, using the cases to illustrate gaps in mandating equitable post-quantum migration. The conclusion reflects upon legal gaps enabling unequal protections, advocating reforms including mandatory quantum risk assessments. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Background. California mandates organic waste diversion, but participation depends on infrastructure and instruction that may be unevenly distributed. Whether socioeconomic disparities in adolescent zero waste engagement reflect unequal access, unequal knowledge, or unequal conviction has not been established.Methods. A cross-sectional survey of 218 middle and high school students across 15 San Francisco Bay Area schools (MarchāMay 2026) measured zero waste knowledge, home and school access to sorting infrastructure, sustainability beliefs, self-reported behaviors, and perceived barriers. Residential ZIP codes were linked to median ZIP-code income (n = 207 matched). Analyses comprised MannāWhitney comparisons and Spearman correlations with BenjaminiāHochberg correction and bootstrap confidence intervals, intraclass correlations by school, hierarchical regression, a mixed-effects model, and an exploratory mediation. Results. Median area income was positively associated with familiarity with the term "zero waste" (Ļ = .26, 95% CI [.12, .38], pāadjā = .002), waste-reduction habits (Ļ = .19, pāadjā = .031), composting frequency (Ļ = .18, pāadjā = .031), and home compost access (Ļ = .17, pāadjā = .042), but not with practical composting knowledge (Ļ = .11, pāadjā = .257), sorting confidence (Ļ = .03), or either belief item (Ļ = ā.06 and ā.08, both n.s.). Income added a small unique increment to composting frequency over demographic covariates (ĪRĀ² = .025, p = .020) but none to knowledge (ĪRĀ²
Time blindness is a common symptom ascribed to individuals experiencing ADHD or the spectrum of ADHD symptoms. However, it is most often characterized as a deficit to functioning properly, whether this is in the workplace, schools, or relationships. Like much of the information surrounding neurodiversity, ātime blindnessā is a gross oversimplification of people with ADHDās felt experience of time. For individuals with ADHD, measuring changes in attention and shifts in chronoception (the perception of time) can be achieved through an analysis of art practice. This paper looks critically at the role that time plays in the lives of neurodiverse and neurotypical people alike.
Active asset managers increasingly include cryptocurrencies in their alternative asset allocations, highlighting their speculative and volatile nature. The aim of this research is to examine trends in the returns and volatility of cryptocurrencies, whilst accounting for the depegging of stablecoins, driven by speculative trading during macroeconomic shocks and technological shifts. We build a sample of market capitalisation, using data from the daily closing prices of Bitcoin (BTC), Ethereum (ETH), Binance (BNB), and Ripple (XRP), two fiat-backed stablecoins (USDT and USDC), and a cryptocurrency-collateralised stablecoin (DAI). As a first step, a Granger-causality framework is applied to examine the influence of stablecoin depegging events on crypto returns during financial market stress. The results are strongly asymmetric: there is little evidence that depegs predict returns; whereas cryptocurrency returns robustly Granger-cause USDC depegging events, an effect that intensifies during periods of market stress. Stablecoin depegs appear to be a downstream symptom of cryptocurrency stress rather than a leading indicator of it. The analysis was extended by modelling volatility, using an EGARCH-X model to study whether depegs also affect crypto during periods of market stress and if larger deviations from the dollar peg are associated with higher cryptocurrency volatility, concentrated in the most liquid stablecoins (USDT and USDC), while the evidence for any change in this association during stress is limited. The findings carry implications for risk monitoring in digital-asset markets, where stablecoin behaviour reflects, rather than anticipates, cryptocurrency market conditions.
Since 2008, when the cryptocurrency was first introduced under the name Satoshi Nakamoto, more and more people are interested in the Ā«new moneyĀ» ā Bitcoin. Bitcoin is the first cryptocurrency and although many other cryptocurrencies were created and will be created in the future, Bitcoin remains the most popular cryptocurrency to this day. Naturally, along with the rapid growth of information technologies and their applications, many new Ā«computerizedĀ» currencies will emerge. Because anyone can buy and sell cryptocurrency (e.g. bitcoin) and, thus, cryptocurrency is a subject of trade, hence cryptocurrency and in particular bitcoin is a product. Naturally, questions arise about the determinants of cryptocurrency price changes. In particular: Are the changes in the prices of cryptocurrency (and in particular Bitcoin) related to the development trends of the global economy? Are changes in the prices of cryptocurrency (and in particular Bitcoin) related to indicators of the state of the global economy, such as the well-known indices DJII, Nasdaq, S&P 500 and others. Thus it is interesting to see whether it is possible to predict changes in the prices of cryptocurrencies (and in particular Bitcoin) using different methods of time series.
This study aims to provide a comprehensive science mapping and bibliometric analysis of the FinTech landscape within Islamic banking and finance. It deciphers the intellectual structure and thematic evolution of the field during the transformative window from 2017 to early 2026. Methodology: Utilizing the Scopus database, a dataset of 725 scholarly documents was extracted and analyzed. The research employs a multi-tool approach, integrating R-Bibliometrix (Biblioshiny) for longitudinal performance analysis and VOSviewer for visualizing keyword co-occurrence and institutional collaboration networks. The PRISMA 2020 protocol was followed to ensure methodological transparency. Findings. The results reveal an exponential surge in scientific production, characterized by an impressive annual growth rate of 28.42%. Malaysia and Indonesia emerge as the primary global knowledge hubs, with the International Islamic University Malaysia leading institutional contributions. The analysis identifies three core intellectual clusters: (1) Blockchain and Cryptocurrencies, (2) AI and Regulatory Compliance, and (3) Financial Inclusion and Institutional Stability. Thematic evolution indicates a strategic shift from basic FinTech adoption toward advanced applications in Artificial Intelligence, Ethical Technology, and the Sustainable Development Goals (SDGs). Originality,
Digital technologies are transforming supply chain management by enabling greater connectivity, transparency, and coordination among supply chain partners. In forestry supply chains, characterized by dispersed resources, multiple stakeholders, and complex operational processes, collaborative governance has become increasingly important for improving coordination and sustainable resource management. However, existing studies mainly focus on operational optimization and digital applications, while the governance implications of digital technologies remain insufficiently explored. This conceptual article explores how digital technologies may enable collaborative governance capability in forestry supply chains through four governance mechanisms: information sharing, resource integration, collaborative decision-making, and adaptive governance. Based on collaborative governance and digital transformation literature, a conceptual framework is proposed to illustrate how digital technologies may support governance processes through the Internet of Things, big data analytics, cloud computing, blockchain, and artificial intelligence. The article provides theoretical insights into digital-enabled collaborative governance and practical implications for sustainable forestry supply chains.
We study auctions where two positions are sold to unit-demand bidders with private heterogeneous order preferences: some are specialists who value only the first position, while others are generalists who are indifferent between the two. First, we consider a standard first-price rule which allocates the first and second items to the highest and second-highest bidders, respectively. We show that no strategy profile ex-post implements the efficient allocation at every type profile, irrespective of payments, and provide a distribution-free equilibrium welfare guarantee of $\frac{1}{2}$. To augment this result, we prove that for deterministic one-round auctions and discrete bids, the efficient allocation requires each bidder to communicate at least one bit more than its bid's binary representation. We next ask what the same bit accomplishes in winner-pays-bid formats where bidders can also specify specific item preferences. In particular, we show that this strengthens our distribution-free equilibrium welfare guarantee to $1-\frac{1}{e}$. Finally, we discuss our results' applicability to priority service auctions and blockchain transaction sequencing.
CyberProtocol AI Trust Standard, Version 1.0 Artificial intelligence now writes, decides, and transacts at global scale, yet the world has no shared way to answer four simple questions about any AI output: who made it, where it came from, whether it is safe, and whether it obeys the law. CyberProtocol is built to answer all four. CyberProtocol is a neutral, open, cryptographic framework for verifying AI Identity, Provenance, Safety, and Compliance across all jurisdictions. It is published as a global public good, aligned with United Nations principles, and is controlled by no nation, corporation, or bloc. The timing is decisive. Three converging mandates now demand verifiable AI: EU AI Act enforcement, the founding of WAICO, and the Rome Declaration by Nobel Laureates. Each requires proof of origin, safety, and compliance, yet no harmonized, cross-border verification standard exists today. CyberProtocol is designed to fill exactly that gap, and to do so immediately, because the building blocks already exist. The Standard defines four verifiable layers that work as one system: AI and Human Identity, using Decentralized Identifiers for AI agents and W3C Verifiable Credentials for people. Provenance and Output Certification, an immutable cryptographic seal on every output, with an optional zero-knowledge mode that proves origin without exposing trade secrets. Safety and Risk Compliance, with metadata mapped to the EU AI Act, NIST AI RMF, and ISO/IEC 42001. Cross-Border Verification, a neutral seal format anyone can validate, tied to no national scheme. CyberProtocol invents no new cryptography. It unifies proven, mature standards into one coherent, interoperable framework, which is why it can be adopted now rather than years from now. The Standard is published and stewarded by One Planet One Earth Foundation Inc., a non-profit holding United Nations ECOSOC Special Consultative Status since 2025 (esango.un.org, profile 695078), (UNDESA Civil Society Database; SEC Registration CN202004649; DSWD-FO III-L-00002-2023). This accreditation gives CyberProtocol a neutral, internationally recognized home, positioned to engage UN member states, regulators, and the Global South on equal terms. As a public good, the Standard is free to all in perpetuity. Advancing it to a working reference implementation, pilot integrations with AI laboratories, and multi-stakeholder governance requires support. The Foundation invites funders, philanthropies, standards bodies, and industry partners to help make verifiable AI a global default. Together we can ensure the AI era is built on trust that anyone, in any country, can verify. Version 1.0, Initial Proposal. Specification under Creative Commons Attribution 4.0 International (CC BY 4.0); reference code under Apache License 2.0. Official reference: https://cyberprotocol.io. Repository: https://github.com/ryanpaulpillas/cyberprotocol-ai-trust-standard. Steward: One Planet One Earth Foundation Inc., holder of UN ECOSOC Consultative Status since 2025.
Solidity has undergone 116 version iterations between August 2015 and February 2026, during which compiler updates have introduced behavioral changes, including issues later fixed in subsequent releases. Contracts compiled under specific versions may exhibit version-dependent execution behaviors, particularly in low-level code. These differences are often difficult for developers and users to recognize, creating opportunities for adversaries to exploit legacy compiler behaviors and deploy contracts with potentially deceptive outcomes. We define this issue as the Compiler Version Discrepancy (CVD) risk , where attackers leverage compiler-version-dependent behaviors to produce misleading or unfair outcomes while contracts appear functionally benign. We summarize five representative CVD risk patterns from real compiler inconsistencies. To mitigate this risk, we develop the CompileGuard detection tool. It combines Abstract Syntax Tree (AST) analysis, taint analysis, and symbolic execution with Control Flow Graph (CFG) analysis to identify version-sensitive code patterns. Evaluation on 227 smart contracts shows CompileGuard achieves an overall F1 score of 95.22%. A user study with 21 blockchain practitioners shows contracts exploiting CVD risks can mislead users, while detection reports enable all participants to correctly identify risk-inducing behaviors. These results highlight the practical exploitability of CVD risks and the effectiveness of automated detection in preventing such deception.
An increasing number of special Internet of Things (IoT) applications are being deployed within federated and zero-trust (ZT) environments. These ad-hoc networks consist of heterogeneous, resource-constrained devices from various administrative domains, all of which are susceptible to compromise. The dynamic nature of these environments necessitates near-real-time Situational Awareness (SA), where processed data varies with its sensitivity and reliability, without dependence on a central authority. Examples include NATO and non-NATO coalitions engaged in hybrid military operations or humanitarian aid scenarios. To address the challenges of security, reliability, and context-aware data dissemination, we propose FedM, a multi-level formal model designed for context-aware and policy-driven data dissemination in federated IoT environments. This model is built upon various access control models and Denningās research on information flow control (IFC), prioritizing the protection and reliability of data flows. A crucial element of this model is the distributed ledger, which facilitates the dynamic modification of label expressiveness, enhances resilience against disruption attacks, and separates policy logic from application functionality to mitigate risks associated with the benevolent developer. Additionally, we delineate a deterministic and history- and precedence-aware policy enforcement procedure to resolve conflicting actions and introduce processing primitives for the ongoing Data Quality Assessment (DQA) process. Our model also aligns with the concepts of Ubiquitous and Continuum Computing. Furthermore, in our paper we illustrate a policy-based dissemination pipeline, incorporating a bounded trustworthiness dimension. Additionally, we present a refined multi-layered framework that proposes the deployment of Information Flow Control (IFC) components, such as the Open Policy Agent decision engine, to facilitate policy-driven contextual data dissemination. We provide preliminary benchmarks for resource-constrained platforms, along with a formal threat model that addresses implicit flows, the benevolent developer problem, and the behavior of a distributed ledger under degraded network conditions. Finally, we conduct a formal verification of our model using the P framework.