Blockchain Papers

Petar Hrgović

No abstract is available for this record.

C. В. Козловський, В. В. Чеботок

The article examines risk management as a strategic foundation for managing the economic activity of an enterprise under conditions of wartime instability, macroeconomic turbulence, and digital transformation. The relevance of the topic is driven by the growing level of environmental uncertainty, intensified competition, and the emergence of new digital and war-related risks that require the formation of an integrated system of strategic risk management. The purpose of the article is to substantiate the theoretical foundations and develop practical approaches to the formation of a risk management system as a strategic tool for managing the economic activity of an enterprise.The paper systematizes the main risk management instruments (risk acceptance, avoidance, transfer, and mitigation), identifies the structural elements of the risk management process, and proposes a model for organizing business processes within the framework of a risk management strategy. The concept of risk zones (risk-free, acceptable, critical, and catastrophic) is disclosed, enabling the assessment of risk concentration levels and ensuring timely adjustments of managerial decisions.Special attention is paid to digital risks arising from the implementation of cross-cutting digital technologies, including artificial intelligence, big data, robotics, and distributed ledger systems. The authors propose an original classification of digital transformation risks at the enterprise level, distinguishing economic, technical, organizational, and war-related risks, as well as identifying key risks associated with the use of artificial intelligence technologies (data privacy risk, infrastructure risk, statistical discrimination risk, incorrect managerial decision-making risk, workforce imbalance risk, etc.). The necessity of integrating digital risks into the corporate risk management system (ERM) is substantiated.The article also considers modern strategic approaches to risk management, including the “three lines of defense” model, the method of defining risk appetite and risk tolerance, and the development of risk culture and effective communication. It is proved that their integrated application creates a holistic risk management architecture aimed at preventive response, balancing profitability and sustainability, and enhancing the economic security of the enterprise. It is concluded that under modern conditions, risk management acts not only as a mechanism for minimizing threats but also as a strategic concept for ensuring long-term stability, innovative development, and competitiveness of an enterprise in the context of the digital economy and wartime challenges.

Matthew Rosendin

No abstract is available for this record.

Martin Brennecke, Simon Mertel, Tobias Guggenberger, Johannes Sedlmeir · 6 authors

Zusammenfassung Auf dem Weg zu einer kreislauffähigen Wertschöpfung nimmt die lückenlose Dokumentation von Produktionsketten eine elementare Rolle ein: Sie erlaubt es, eingesetzte Ressourcen und Schritte im Wertschöpfungsprozess nachzuvollziehen und nachhaltigkeitsbezogene Angaben überprüfbar und somit vermarktbar zu machen. In diesem Kontext wird immer wieder über die Blockchain-Technologie diskutiert. Neben den Chancen, die eine Blockchain für eine verifizierbare Dokumentation und Interaktionen über Organisationsgrenzen hinweg bietet, werden in diesem Beitrag die Herausforderungen ihrer Nutzung aufgezeigt. Dabei wird auch auf komplementäre Technologien, insbesondere kryptographische Ansätze für digitales Identitätsmanagement und Zero-Knowledge Proofs, eingegangen und gezeigt, wie diese zur Bewältigung der Herausforderungen genutzt werden können.

Mrs.Dhanalakshmi.J, Gokul Pandi.P, Gurumoorthi.P, Ragul Pranav.A

Traditional and electronic voting systems face significant challenges in ensuring transparency, security, and voter trust. Issues such as centralized control, lack of auditability, vulnerability to tampering, and potential for fraud undermine the integrity of electoral processes. This paper proposes a novel blockchain-based electronic voting system designed to address these shortcomings through decentralized ledger technology and smart contracts. The system ensures vote integrity, voter anonymity, and public verifiability while preventing double voting and eliminating single points of failure. By employing cryptographic techniques such as zero-knowledge proofs and ring signatures, voter privacy is maintained without compromising transparency. The proposed architecture is evaluated through simulation, demonstrating scalability, reduced transaction costs, and robustness against common cyber threats. This work contributes to the advancement of trustworthy digital democracy and provides a feasible framework for real-world electoral deployment.

Yujia Xian

The concept of blockchain has transformed the trust concept by decentralizing, non-modifiable, and transparent, but there is a certain conflict between the principle of public verifiability and data privacy. As DeFi and cross-institutional data collaboration should grow, it has become a fundamental concern to have the confidentiality of this data without losing verifiability on-chain. The following paper will be a review of blockchain privacy technologies developed in 2020-2025, which will involve the history of zero-knowledge proofs and homomorphic encryption development at the cryptographic primitive level, as well as share new developments such as secure multi-party computation. It points out advances in recursive proof systems, distributed proof generation architectures and scalable multi-party computing systems to overcome bottlenecks in performance. There is a trade-off between privacy, system performance, regulatory compliance, and decentralization in a comparative analysis of technology integration in both public and permissioned chains. Lastly, research directions in the future are suggested in order to overcome issues associated with low proof efficiency, regulatory compliance problems, and migration of post-quantum cryptography. The review offers both theoretical and technical sources on how to develop trusted blockchain infrastructure that would strike the right balance between compliance, high-performance, and data sovereignty.

Gunjan H. Deshmukh, Mahesh R. Sanghavi

Advancements in networking applications increase the requirement for secure data storage and an efficient data access mechanism with robust networking characteristics. Consequently, the huge volume of data generated from the het-erogeneous networks, such as smart cities, healthcare, and smart energy trading systems, suffers from scalability issues and generates insights for secure data storage and effective data management. Therefore, the research proposes a secure data storage and access scheme named Multimodal Biometric-enabled Zero-Knowledge Proof of Stake(MBZKPS). The Multimodal Biometric Data Access(MBDA) ensures secure and robust access to the heterogeneous data with reduced computational overhead. The Distributed Storage System and the Zero Knowledge Protocol with Proof of Stake alleviate the storage pressure on the blockchain and regulate the heterogeneous data storage and access in the blockchain. The Message Digest 5(MD5) with Homomorphic Encryption enables computations on the encrypted data with better data confidentiality preserva-tion. The introduction of the blockchain eliminates the scalability issues with improved privacy preservation and data integrity. Simulation results validate the superiority of the MD5 with Homomorphic Encryption (HE) used in research by achieving 0.95ms decryption time, and 0.97 encryption time with 0.73 Genuine User Rate occupying 363.76KiloBytes of memory for 250 nodes. In addition, the proposed research performs secure data storage with a 1025.85 ms response time and 1.01ms transaction time using blockchain.

Sonia Shahid

No abstract is available for this record.

C.A. Bindyashree, Chitra G., Syed Muzamil Basha, Hamed Taherdoost

In the present times, Transformation finance has become a prominent approach for a systematic financial channel to facilitate the step-by-step decarbonization of carbon-intensive sectors. Such mechanisms rely on the accuracy of carbon emissions data to measure environmental performance and to inform capital decisions. The current carbon accounting methods are limited by inadequate data-collection provisions, slow verification processes, and low auditability, which undermine the reliability of emission-reduction claims and constrain the effectiveness of carbon asset markets. In the present research work, a blockchain-based framework is proposed that will create reliable carbon data accounting and facilitate structured carbon asset circulation within ecosystems of transformation finance. The framework establishes a single carbon lifecycle for data, integrating real-time emission tracking, multi-step verification, a secure registry, and computer-generated assets. The datasets of industrial emissions used to test the operation of the proposed system under multi-sector conditions include energy systems and manufacturing activities, logistics networks, and urban service infrastructure. The objective of the proposed framework is to measure the reliability of carbon accounting by normalizing emission intensities, estimating verification confidence, and scoring trust with uncertainty. In addition, a circulation model is proposed to describe the liquidity of carbon assets, the efficiency of their utilization, and the stability of decentralized transactions. The outcome of the present research is to regulate the creation and transfer of tokenized carbon assets, which guarantees the consistency of environmental performance and financial representation. The review shows a quantifiable increase in the visibility of emission records, a decrease in verification delays, and greater visibility into asset circulation processes compared with traditional centralized systems. The suggested framework establishes a logical link between verifiable carbon-reduction results and decentralized financial mechanisms, enhancing the operational feasibility of transformation finance.

Jie He, Haiyan Cheng

Effective risk management has grown more and more crucial in the complex world of international trade finance, bolstered by security, trust, and openness. By creating an integrated system that blends Hyperledger Fabric blockchain technology, Supply Chain Finance (SCF) protocols, and Generative Adversarial Networks (GANs), this study seeks to improve the intelligence and dependability of financial risk assessment. Four interrelated steps make up the suggested approach: (1) preprocessing and encoding SCF datasets; (2) creating synthetic risk data with GANs to mimic uncommon or dishonest trade behaviors; (3) using Hyperledger Fabric to execute smart contracts and log transactions decentralized; and (4) using real-time SCF compliance modeling for dynamic risk assessment. While blockchain guarantees the transparency, immutability, and auditability of financial records, GAN integration improves the prediction model by adding value to the training corpus. Comparative studies show that the suggested system considerably lowers the likelihood of data tampering and improves risk prediction accuracy by 12% when compared to traditional machine learning models. The results demonstrate that integrating generative modeling with blockchain technology can significantly improve financial risk management, transparency, and adaptability in global trade settings.

Sara Gace, Julian Rode

The Vjosa River Basin, located in the heart of the Balkans, is one of Europe's last free-flowing wild rivers comprising a large number of pristine habitat types with a wealth of biodiversity. Widespread degradation of the forest ecosystem and unsustainable land use due to logging and livestock farming have led to an urgent need for effective conservation planning and sustainable management. This study applies the Ecosystem Service Opportunity (ESO) framework to provide a diagnosis of the social-ecological context and the current institutional and legal frameworks governing the Vjosa River in Permet area and its surroundings. Based on 15 semi-structured interviews with stakeholders from local government, NGOs, and a national government agency, we identify opportunities for policy and finance instruments to encourage ecosystem conservation and sustainable livelihoods. The results are compared to Integrated Management Plan (IMP) for the Vjosa Wild River National Park. Our results align with the IMP approach in several strategic areas (i.e., stronger law enforcement and patrolling, regulating illegal livestock grazing, improved staff management and collaboration between local agencies, incorporating traditional knowledge in conservation strategies), but further emphasizes the need for action beyond national park boundaries, decentralization with stronger municipal involvement, establishment of a collaborative platform, and the diversification of funding initiatives.

Balaram Tripathy

Enterprises are rapidly shifting from human-interpreted dashboards to Autonomous Analytical Entities (AAE) that execute decisions directly on production systems. This transition introduces a new failure mode—Agentic Divergence—where decentralized agents act on misaligned, drifted, or out-of-scope data products and metadata, leading to high-impact errors at scale. This paper proposes the Autonomous Analytical Coherence (AAC) framework, centered on an Analytical Control Plane (ACP) that inserts a mandatory, machine-enforced governance layer between AAEs and decentralized data products. The ACP mandates Agentic Data Contracts (ADC) as runtime dependencies and enforces Kullback–Leibler (KL) divergence-based drift checks within Trusted Execution Environments (TEE) to safeguard both analytical coherence and data sovereignty. Simulation-based experiments across finance and logistics workloads indicate that AAC reduces erroneous autonomous transactions by 77% compared with uncoordinated agent deployments, with only a 25 ms median increase in latency. These results demonstrate that treating governance as a runtime dependency is a practical path toward safe, high-stakes autonomous analytics in enterprise data meshes.

Radovan Vladisavljević, Aleksandra Zlatić-Tešić, Svetlana Marković

The aim of the work is to present a model of tax control automation using smart contracts, this is a relatively new application of blockchain technologies. The use of new technologies can greatly improve the operations of modern organizations that have digitized their operations. New technologies not only provide a high degree of automation but also provide a high degree of transparency. This leads to faster business with an increase in the level of trust of all participants in the business venture.

Elvira Albert, Samir Genaim, Enrique Martin-Martin

Abstract Many compilation stages of smart contracts on the Ethereum blockchain have been transitioned to the intermediate language . Tasks such as smart contract optimization and bytecode generation are—or will soon be—performed directly at the level in the compilers for the higher-level languages such as Solidity. In this paper, we develop a formal semantics of programs in Rocq, suitable for verification, which allows formal reasoning at the level of code or generation tools processing programs. Our semantics is expressive enough to be the basis for formal verification tools, and simple enough to make the development of such tools feasible. In order to prove its adequacy for verification, we develop in Rocq a checker (and associated soundness proofs), based on our semantics, able to verify the results of the liveness analysis stage of the official Solidity compiler , which opens the door towards formally verified Ethereum’s smart contracts compilation. Experiments on more than 1,500 smart contracts show that we are able to automatically verify ’s liveness analysis results in negligible time.

Andrea Stazi

The incessant development and ubiquitous diffusion of information and communication technologies give rise to phenomena of considerable socio-economic and therefore legal significance. Among these, contractual relationships are strongly affected by technological evolution, which provides new tools for negotiating, concluding and executing contracts, with specific operating dynamics and unpublished legal issues. In this perspective, from a legal point of view, the contract-technology combination represents a topical issue for a comparative analysis, which provides the interpreter with an overall view of different local responses to common developments and problems deriving from the use of technology in contracts.

Arseniy Vladimirovich Svetskiy

The article is devoted to the philosophical, legal and comparative legal analysis of the transformation of the autonomy of the will in the context of algorithmization of private law. The subject of the study is the transformation of the autonomy of the will as a system-forming principle of private law in the context of algorithmization of contractual relations. The focus is on the relationship between automaticity of fulfillment of obligations (smart contracts) and dispositivity, as well as the functional change in the role of the subject of civil law in the digital environment. In this paper, attention is paid to the problem of the relationship between automaticity of fulfillment of obligations and dispositivity as a system-forming principle of contract law. The author proceeds from the historiographical understanding of the autonomy of the will, which has developed in European and Russian civil law, and considers the smart contract as a technological form of realization of the previously expressed will of the parties. Additionally, the limits of judicial control and the preservation of traditional principles of good faith and proportionality in algorithmic mandatory structures are analyzed. The research methodology is based on a combination of philosophical-legal and comparative-legal approaches. The author applies a formal dogmatic method to analyze the category of autonomy of will and the legal nature of a smart contract in Russian civil law. The scientific novelty of the article lies in substantiating the thesis that the algorithmization of private law, contrary to the doctrinally widespread ideas about the "death of the subject" and the replacement of the autonomy of the will by program code, leads not to the denial of the classical model of the contract, but to the functional transformation of the role of the subject. Based on a comprehensive comparative legal analysis (Russia, the countries of continental Europe, the USA, China), the predominance of an integration regulatory model has been revealed, in which a smart contract adapts to existing legal structures without revising the conceptual core of the law of obligations. A comparative legal analysis of the regulation of smart contracts in Russia, the countries of continental Europe, the USA and China demonstrates the predominance of an integration model in which digital technologies adapt to existing legal structures without revising the conceptual core of the contract. The conclusion is drawn that the subject of private law in the era of algorithms does not lose its autonomy, but becomes the architect of its own digital normativity, while maintaining the status of a bearer of will and legal responsibility.

Maria Smith

[Depreciated and replaced by V3] The application-specific clean rebuild has not yet been published; its authoritative theoretical boundary is now the governing V3 branch: After Turing: The Fold Machine - An Exact, Parameter-Free and Machine-Closed Derivation of Classical Computational Science from Smithian Fold Theory; From Fold to Consciousness: An Exact, Zero-Parameter and Machine-Closed Foundational Reconstruction of Consciousness and Cognitive Science from Smithian Fold Theory. The V3 source platform is https://github.com/MettaMazza/ernos-labs-sft-platform. The original DOI, concept DOI, version number and files are preserved for transparent historical provenance; this record must not be presented or cited as current V3 work. v4.0 — the word-scale gap closes within the fold. Rung 5e (pre-registered): the fold-factor mixing law — every context level that holds contributes, weighted 2^level, the engine's own forced halving constant — carries the pure counted engine, with no twin, no prose flood, zero training and zero parameters, past the gradient-trained transformer at word scale: cross-entropy 3.1907 vs the same-day twin's 3.4292 (replicated across two independent anchorings; stacked with the Rung 5d extraction: 3.1344). Both scales of the task gate now belong to the counted engine. Rung 5d's transfer-in verdict is SUPPORTED across three independent arena anchorings in one day. New in the architecture: tool graduation (acts held, values never — a question territory that a tool answered once runs the tool itself thereafter, fresh), recall as regeneration across every memory tier, and judge-independent graduation scoring. End-to-end verification: 36/36. v3.4: Rung 5d, the transfer-in — pre-registered verdict SUPPORTED: the trained twin's dyadically-loud fold content is extracted and installed INTO the counted engine as a counted prior with zero new parameters, closing 55.6/87.9/101.4% of the available gap at k=16/32/64 while the random-truncated null closes 10.1/24.5/56.5%; at half budget the loud shape beats the full twin's own. The word-scale rematch is recorded in full (twin retrained on today's text; decomposition included). Also: judge-independent graduation scoring (boot-discovered pool, cycle-parity alternation), multi-orbit binding (XI-4 in full), recall-is-regeneration (a held experience re-walks its own orbit, never reprinted), the public SOTA table beside the local giants with cited published figures, and one-command replication kits (GPT-2 weights auto-fetch; 13/13, 39/39 proven on a fresh clone). End-to-end verification: 36/36. Full paper v1.1 — supersedes the pre-paper (From One Axiom to Master-Level Chess — and the Law Inside Neural Networks). Built from scratch by one woman, working alone, in under twenty-four accumulated hours: where a score falls short it marks an implementation gap at measurement time, never a limit of the mathematics — the gains between releases are the finding. v1.4 adds the fold eye (vision as exact integer Walsh spectra, self-certified by integer Parseval per image, recognition of seen images with no image model in the loop) and the graduation score (blind head-to-head vs the teacher, tallied per question-territory; the teacher retires as wins cross the majority lock) -- and documents the 2026 convergence: DeepSeek Engram arrives at deterministically-addressed exact memory from the gradient side, and two independent results place the optimal curriculum at p = 1/2, the fold lock. v1.6: the full omnimodal engine (the voice via Kokoro, the fold ear -- sound as Parseval-certified integer Walsh spectra, video composed from frames + sound), speaker-transparent reasoning threads, and 32/32 end-to-end empirical verification of the entire architecture including persistence across process death. v1.7: removal-proof omnimodality, measured -- every supporting model is a teacher with an exit: a sound taught once by the synthesis teacher is re-spoken from the engine's own exact counted record in 0.00s with no model; a sound heard once is recognized natively with no transcriber; 34/34 end-to-end verification. v1.9: zero-model perceptual learning (the human observer -- a novel image learned and re-recognized at share 1.00 with no model in the loop); agentic self-knowledge (the observer reads the engine's own source, measured); the hourly progress instrument with a committed pre-boot birth line; one-tap y/n closure. v2.0 (flight-ready): the full modern-agent toolkit (live web search/fetch, paginated reading, in-file grep -- every call held as a training trace), the 43-domain everything-curriculum under the fold-only law, SOTA 1-1 benching on the public MMLU test split with the newborn baseline committed, generation closure (the Learning Law reaches generate() itself), and 36/36 end-to-end verification. v2.1: the ReAct law (reason-act-observe enforced in-turn; narrated intent without an act is detected and forced), reasoning trained on the observer's NATIVE thinking tokens (STaR-gated) with both minds' full thinking streamed to the user, and document intake (a sent file is reading -- inboxed, counted, persistent). v2.2: the identity stated correctly -- UnisonAI is an OMNI MODEL (language, sight, hearing, speech, and video on one held memory), not a language model; LLMs remain the contrast class only. v3.0: the full-altitude rewrite -- the complete omni model documented at the same depth as the spectral science: thirteen sections, the architecture organ by organ with every measurement, Rung 5c as its own section, the empirical record and its committed birth line, 36/36 end-to-end verification, and the 2026 convergence. This paper is a PROOF of The Smithian Fold Theory of Everything, not the main event: the theory (one axiom, zero free parameters, 1,844 machine-verified forced checks) is at DOI 10.5281/zenodo.21182469 and github.com/MettaMazza/Smithian-Fold-Theory-Of-Everything -- run the prover yourself. The engine: github.com/MettaMazza/UnisonAI. v3.3: the LLM-native presence suite -- the exact registered protocol applied to GPT-2's entire knowledge-storage class: 13/13 tensors, 39/39 checks, unanimous (margins 3.4-79.3x); the flagship claim now rests on the flagship objects, with diffusion/speech models recast as cross-domain breadth. Three connected results and the architecture they force. First, a pre-registered, self-certifying spectral instrument shows trained neural-network weights carry placement-law in the dyadic (Walsh) basis: 18/18 unanimous on validated released models; the law concentrated in transformer expansion projections and token embeddings across three unrelated architectures (up to 230x chance in GPT-2), attention at chance; strictly training-caused (He-initialised controls at 1.0x); surviving 4-bit deployment quantization. A recipe map from 124M to one trillion parameters shows the law tracks training recipe, not scale or architecture — strongest carrier DeepSeek-R1-671B at 43–47x — and loud-recipe weights transform under the fold's transformation group exactly as solved game-theoretic value fields do. Second, the "learned similarity space" is a counted object: word kinship as exact co-occurrence shares reproduces semantic family structure (quark → lepton, neutrino, proton) with zero parameters and zero gradients. Third, UnisonAI: a complete language architecture in which every LLM mechanism — memory, attention, similarity, learning, prediction, generation — is replaced by a machine-verified law of the Smithian Fold Theory, zero trained parameters end to end. On identical held-out text the fold-native engine outperformed its trained transformer twin (cross-entropy 1.289 vs 1.888) after reading the corpus once (26 seconds) against 48,000 gradient readings (21 minutes per seed). Deployed as a live, continuously-learning agent whose teaching loop also runs autonomously: a teacher model asks, judges, and closes the learning law itself, and the engine self-plays against its own held lessons. Negative results reported in full with their scopes. Companion to The Smithian Fold Theory of Everything (DOI: 10.5281/zenodo.21182469; 307 suites, 1,844 forced checks, 0 failures). Engine and records: github.com/MettaMazza/UnisonAI and github.com/MettaMazza/Smithian-Fold-Theory-Of-Everything.

Shashank Kumar

We present CHRONOS, the first autonomous AI agent that simultaneously achieves plaintextblindness (all data is processed under fully homomorphic encryption without ever beingexposed), cryptographically enforced time bound existence (the agent’s own decryption key islocked behind a publicly verifiable proof of sequential work, rendering it inaccessible until aprecise future moment), and remote verifiability of self destruction (a zero knowledge proofcertifies that the key material has been irreversibly destroyed after mission completion). Theagent’s operational lifespan is governed by a “cryptographic fuse” constructed from a proof ofsequential work (PoSW) whose computation time accurately matches the intended missionduration. A drand decentralized randomness beacon serves as a trusted time oracle to trigger thefinal key shredding. Crucially, the erasure proof is a non interactive zero knowledge argument(SNARK) that proves the correct execution of the entire self destruction sequence—including thePoSW solution, decryption of the private key, and subsequent memory zeroization—enablingany third party to cryptographically verify the agent’s annihilation without trusting the agent orits hardware. We provide a complete system architecture, a formal security model with gamebased definitions and reductions to standard assumptions, and a proof of concept implementationusing Zama’s TFHE rs for encrypted inference, a Cohen Pietrzak PoSW implementation, and aGroth16 SNARK. Our benchmarks indicate that FHE inference on a small neural network (50 Kparameters) completes in seconds, the PoSW background thread consumes negligible resources,and the erasure proof can be generated and verified in under three seconds. CHRONOSrepresents a fundamental advance in secure, disposable AI agents, with immediate applications indefense, intelligence, and high privacy environments.

Daiki Miyahara, Pascal Lafourcade, Maxime Puys

Card-based zero-knowledge proof (ZKP) protocols allow a prover to convince a verifier that it knows a witness of a given statement, without revealing any information, using a physical deck of playing cards. Previous studies have focused on puzzles with a specific connected component, such as a simple cycle and a polyomino. In this study, we propose a unified approach to handle a family of connected components, including a tree, path, cycle, and polyomino. This approach achieves this verification in O(mn) steps relative to a given grid size m × n. Using this approach, we construct a card-based ZKP protocol for Nurimeizu, where the goal is to find the shortest path on a given grid.

Roman Burtsev

A unified, computationally reproducible framework built on a single ontological method: KTR (Knowledge Triangle Route). It operates on a three-state topological cell (1-0-1), where '0' acts as an active transit, and two corners merge to generate the third (A+B→C, the Chomsky merge) at the root. This closure allows geometric spectra to be translated into algebraic forms. Core Dimensions: Fundamental Physics & Math: Koide through star geometry (Q=2/3 as half-weight, cos²θ=1/2; the electron reproduced to a number within 0.07%, a live falsifiable tau prediction). Structural models for the mass gap, confinement, hadron/penguin, junction, neutrino, star formation, Born rule; and structural accounts of the Millennium Problems (Yang-Mills, Riemann, Hodge, Navier-Stokes, P vs NP, Birch). Information Theory: Applies the Kolmogorov view (randomness as compressibility) via ternary 1-0-1 encoding. Data treated as structured blocks navigated by hash addressing. Quantum Logic: The Qutrit Map Solution (QMS), ternary logic gates, the qutrit cell, zero-mode mass gap analytics. Reproducible computation, executable proof. Computed results (stones) are labelled apart from models; no Millennium problem is claimed solved. Given for those who find use in it.

Krishna C.V.

Sustainable Development Goals (SDGs) emphasize inclusive, equitable, and environmentally sustainable growth, requiring effective localization for meaningful outcomes. Local governments, particularly in developing countries, play a crucial role in translating global goals into actionable strategies at the grassroots level. In India, Panchayati Raj Institutions (PRIs) and Urban Local Bodies (ULBs), empowered by the 73rd and 74th Constitutional Amendments, serve as key agents in implementing SDGs through decentralized planning, resource allocation, and community participation. This research article examines the role of local governments in achieving SDGs in India, with a special focus on Karnataka. Using a narrative review methodology based on PRISMA-ScR guidelines, the study synthesizes findings from 28 empirical studies, government reports, and policy documents published between 2015 and 2026. Evidence suggests that local governance interventions have improved service delivery outcomes by 30–50 percent in sectors such as water management, sanitation, renewable energy, and rural livelihoods. Initiatives such as Gram Panchayat Development Plans (GPDPs), e-Gram Swaraj, and Finance Commission grants have strengthened participatory planning and accountability. However, challenges such as limited fiscal autonomy, capacity deficits among elected representatives, and coordination gaps persist. The study concludes that strengthening local governance through capacity building, financial empowerment, and technological integration is essential for achieving SDGs. Karnataka's innovative practices demonstrate the potential of decentralized governance in driving sustainable development.

Md. Al Amin Alamin, Sabekun Nahar Setu

This research investigates the barriers to effective climate finance in Bangladesh, a Least Developed Country (LDC) highly vulnerable to climate threats such as sea-level rise, cyclones, salinity intrusion, and flooding. Despite receiving a significant share of international climate funds for LDCs, Bangladesh faces persistent challenges including complex access procedures, reliance on loan-based financing, institutional limitations, and centralized governance. The study examines Bangladesh's legal and institutional frameworks, including the Bangladesh Climate Change Strategy and Action Plan (BCCSAP) and the Climate Change Trust Act 2010, alongside constitutional and judicial environmental commitments. Findings reveal systemic issues such as limited local participation, donor-driven management, and concerns over debt sustainability. Key recommendations include shifting towards grant-based finance, expanding legal standing for environmental litigation, decentralizing fund access to local governments, and enacting a dedicated Climate Change Act. The study underscores the imperative for Bangladesh to embed climate justice within its legal and financial systems and to advocate strongly in international climate forums. This research contributes valuable insights to the global discourse on climate justice and resilience for the most vulnerable nations.

Helene Natalia Hall

This thesis examines the implications of market frictions in international finance and macroeconomics in three contexts. The first chapter documents the effect of trading relationships on client trading outcomes in the over-the-counter (OTC) foreign exchange (FX) derivatives market. The second chapter documents the effect of nominal wage setting frictions on employment. The third chapter examines the behavior of non-U.S. central banks when firms engage in currency mismatch, borrowing more in dollars than given by their dollar operating exposures, emphasizing how imperfect regulation may affect U.S. dollar interest rates. In the first chapter, joint with Gerardo Ferrara, I study whether clients that rely more heavily on a dealer in the OTC FX derivatives market have worse trading outcomes after the dealer is adversely shocked. Using granular transaction-level data, we document that trading relationships are persistent—in an active trading week, clients are more likely to trade with a dealer that they had a relationship with and relied on more heavily. Then, we exploit the March 2023 collapse of Credit Suisse as an exogenous shock to exposed clients’ set of trading alternatives when relationships are persistent. Using difference-in differences analyses, we find that, although Credit Suisse’s EURUSD notional traded and trade count declined, clients that relied less heavily on Credit Suisse did not differentially reduce their Credit Suisse-specific trading activity relative to more reliant clients. Instead, more reliant clients continued trading at the client level and increased activity with other existing dealer relationships without incurring additional costs, relative to less reliant clients. These findings suggest that search and bargaining frictions were not particularly costly for heavily reliant clients after the shock—relationship persistence did not differentially prevent them from reallocating activity to existing alternative dealers, or lead to relatively greater costs, when their relationship dealer came under stress. In the second chapter, joint with Gert Bijnens, Hugo Monnery, and Laura Nicolae, I empirically document the effect of wage changes, driven by wage indexation to inflation, on firm-level employment growth. In Belgium, nearly all employees’ wages are indexed to inflation and firms are grouped into labor agreements that determine the exact timing and frequency at which wages are indexed, e.g. every year or every month. Using firm-level administrative data, we estimate two-stage least squares regressions of firm-level employment growth on wage growth, instrumented by the wage growth implied by the firm’s indexation policy. We find that employment contracts by 0.4% over four quarters for each 1% increase in wages. This result is robust to including NACE sector-date fixed effects and to using only variation in firms’ indexation timing, controlling for their chosen indexation frequency. About one-third of the response comes via anticipation of future wage increases. The elasticity is more than twice as large in magnitude in the post-pandemic period than before it, suggesting strong nonlinearities. Overall, these results show that, by preventing inflation from reducing real wages, inflation indexation reduces employment. In the third chapter, joint with Mitali Das, Gita Gopinath, Taehoon Kim, and Jeremy Stein, I document an externality of central banks’ imperfect regulation of firms that engage in currency mismatch, which results from central banks’ dollar reserve accumulation decisions. We explore how foreign central banks behave when firms engage in currency mismatch. Using a panel of 56 countries, we document that central bank holdings of dollar reserves are correlated with the dollar-denominated bank borrowing of their non-financial corporate sectors. Then, we build a model in which the central bank can deal with private-sector mismatch, and the associated risk of a domestic financial crisis, by: (i) imposing ex ante financial regulations; or (ii) accumulating dollar reserves to serve as an ex post dollar lender of last resort. The model highlights a novel externality: individual central banks may over-accumulate dollar reserves, relative to what a global planner would choose. Under imperfect regulation of currency mismatch, individual central banks do not internalize that their hoarding of reserves exacerbates a global scarcity of dollar-denominated safe assets, which lowers dollar interest rates and encourages firms to further increase the currency mismatch of their liabilities. Relative to the decentralized outcome, a global planner may therefore prefer higher capital requirements and reduced holdings of dollar reserves.

Christian Kaps, Serguei Netessine, Vishrut Rana, Ömer Karaduman

No abstract is available for this record.