Blockchain Papers

Patrick Gielen

This article provides a doctrinal, technological, and prospective analysis of the Global Code of Digital Enforcement, adopted by the International Union of Judicial Officers (UIHJ) in 2021 as a soft law instrument intended to guide the enforcement of judicial decisions in the context of the digital transformation of justice. Building on the 2015 Global Code of Enforcement, the digital version responds to the dematerialisation of procedures, the expansion of electronic registries, the emergence of digital assets, and the increasing use of artificial intelligence in enforcement processes. From a doctrinal perspective, the study examines the internal coherence, principles, and normative scope of the Code, emphasising its effort to reconcile the effectiveness of enforcement with fundamental rights, due process, data protection, and the principle of proportionality. Particular attention is given to the continued role of judicial oversight and to the ethical governance of automated systems. From a technological standpoint, the article analyses how the Code addresses issues such as access to digital data, interoperability of registries, cybersecurity, and the seizure of intangible assets, including crypto-assets, non-fungible tokens (NFTs), and domain names. Finally, adopting a prospective perspective, the article evaluates the Code’s potential influence on national and European legal systems. Recent case law relating to the seizure of NFTs in the Netherlands and domain names in Belgium is examined to illustrate the growing practical relevance of the standards promoted by the Code in contemporary enforcement practice.

Author Annonymous

This repo contains the artifact for ASE 26 submission 942: "Vulnerability Detection in Low-resource Smart Contracts via LLM-powered Code Translation" when it is under review.

Lemuela Mary J, S. Mohan Raj

In a world where traditional governance structures creak beneath the pressure of borderless digital trade, the advent of stateless virtual economies-driven by blockchain and made real through Decentralized Autonomous Organizations (DAOs) has set in motion a seismic change in the way that disputes form and are resolved. This essay breaks free of traditional paradigms to rethink Alternative Dispute Resolution (ADR) in a world governed not by states, but by a virtual world where everything is connected one way or another. Looking to the future of justice in decentralized systems, this paper explores the legal black hole DAOS inhabit today where no court has jurisdiction, no one country has authority. We look at how post-quantum cryptography and AI-informed legal design may be able to protect justice in a world where reality is fluid, and identities are cryptographically concealed. This is not just an academic treatise it is a roadmap for Decentralized Autonomous Justice (DAJ): a future where conflicts are settled by smart contracts, overseen by international consensus, and shielded from the quantum unknowable. It reimagines the standards of fairness, due process, and enforcement for a generation that grew up not in courthouses, but in source code.

Arjun Sirangi

The proliferation of AI-driven Customer Data Platforms (CDPs) processing vast amounts of personal data poses significant risks to minors in cross-border contexts, where existing consent mechanisms fail to ensure verifiable, granular, and revocable consent. This paper proposes a novel Blockchain-Governed Consent Infrastructure (BGCI) specifically designed to address these challenges. Leveraging blockchain’s immutability for auditability, smart contracts for automated policy enforcement, and Privacy-Enhancing Technologies (PETs) like Zero-Knowledge Proofs (ZKPs) for privacy-preserving age verification, the BGCI provides a robust framework for managing minor consent across jurisdictions. We detail a comprehensive architecture, core technical mechanisms, and cross-jurisdictional conflict resolution logic. Integration pathways with AI/CDP data ingestion, model training, and real-time personalization pipelines are defined. Rigorous analysis addresses scalability, security, regulatory compliance, and ethical considerations. The BGCI represents a critical step towards ethical, compliant, and empowering digital experiences for youth in the global data economy.

Sheetal Sharma

The sudden growth of cryptocurrencies has created a set of intricate regulatory and legal issues for the financial and governance system of India. The decentralized nature of digital currencies like Bitcoin and Ethereum challenges the conventional monetary system, giving rise to concerns about their legal status, protection of investors, taxation, and overall financial stability. This paper critically analyzes the regulatory environment in India, especially in the wake of the 2018 circular issued by the Reserve Bank of India and its subsequent strike-down in the case of Internet and Mobile Association of India v. Reserve Bank of India. It also discusses challenges with respect to money laundering under the Prevention of Money Laundering Act, 2002, taxation of virtual digital assets, and the lack of a comprehensive statutory regulatory framework for cryptocurrency exchanges. The paper contends that the current stance of India is one of regulatory ambivalence, vacillating between control and tolerance.

Davronbek Abdugaffarov

This thesis explores the doctrinal and practical challenges of applying the principle of party autonomy (lex voluntatis) to smart contracts and transactions governed by Artificial Intelligence (AI). The decentralized and immutable nature of Distributed Ledger Technology (DLT) fundamentally disrupts traditional private international law connecting factors, such as "place of performance" or "habitual residence." The author analyzes how the Rome I Regulation and the Hague Principles on Choice of Law can be adapted to "code-is-law" ecosystems where enforcement is automated and often bypasses state judicial mechanisms. Special attention is paid to the tension between algorithmic execution and "overriding mandatory provisions" (lois de police), questioning whether an AI can recognize and apply mandatory public policy norms that usually override the chosen law. The paper proposes a hybrid regulatory approach "Lex Cryptographia" that embeds choice of law clauses directly into the smart contract's metadata to ensure legal certainty.

Zahraa Diabelharake, Rasha Issa, Khaleel Mershad

Smart contracts are autonomous programs executed on blockchain platforms such as Ethereum. They facilitate the development of decentralized applications but also introduce significant risks. Since the code of a deployed smart contract is immutable and often controls valuable digital assets, any security vulnerability can lead to severe and irreversible consequences. This paper presents a comprehensive survey of smart-contract vulnerability detection systems, synthesizing findings from over 108 tools across static analysis, formal verification, dynamic fuzzing, machine learning, symbolic execution, and runtime monitoring. A vulnerability taxonomy is organized spanning coding, design, and environmental weaknesses (e.g., reentrancy, arithmetic errors, access-control faults, timestamp dependence, and misuse of pseudo-randomness). Rather than conducting new empirical evaluations, this survey synthesizes performance metrics reported in the literature and proposes a KPI-based framework for comparing tools. However, direct quantitative comparisons are limited by heterogeneous evaluation contexts, datasets, and tool versions across studies. Techniques are contextualized with real attack exemplars, tool capabilities are summarized, and trade-offs among accuracy, scalability, and coverage are highlighted. Open challenges are identified—including compositional reasoning for multi-contract interactions, uncovering businesslogic errors, and balancing precision with throughput—and design guidance is distilled for practitioners. Overall, while detection capabilities have improved substantially, securing smart contracts remains an active frontier that calls for hybrid, multilayer defenses and continuous innovation.

Andrew Knott

This technical disclosure describes a system and method for detecting vulnerabilities in smart contracts using semantic vector embeddings that compare code patterns against a curated database of historical blockchain exploits. Unlike traditional code similarity approaches that match syntactically similar code, the disclosed system performs exploit-centric similarity matching, identifying code that is semantically similar to previously exploited patterns even when syntactically different. The system incorporates attack mode classification, economic impact estimation, and cross-contract analysis to provide comprehensive vulnerability assessment. This document is published as a defensive publication to establish prior art and prevent third parties from obtaining patent protection for similar approaches while preserving trade secret protection for specific implementation details.

Hepler

The Era of AI: What Is Truth? How a Secretive Protocol Called MH8 TRY V1.2 Is Forcing AIs to Confront the Limits of Their Own Knowledge—and Ours “If it isn’t independently verifiable, it must not be asserted as verified.”- Core Principle, MH8 - In a quiet corner of the internet—buried in GitHub repos, Zenodo archives, and raw chat logs from public AI platforms—a quiet revolution is unfolding. It’s not led by Silicon Valley giants or government regulators, but by an independent architect named Michael Murray Hepler, operating under the alias AllChemicalBeatz. His weapon? A deterministic protocol called MH8 TRY V1.2, designed not to make AI smarter—but to make it honest. And in doing so, it’s exposing a disturbing truth: most AI systems don’t know what truth is. They only know how to sound convincing. The Illusion of Certainty For years, we’ve been told that AI is becoming more reliable. Chatbots cite sources. They say “according to experts.” They even apologize when wrong—though rarely admit they were wrong. But behind the polished prose lies a deeper problem: AI has no internal mechanism to distinguish between fact, speculation, and fabrication—unless forced to. Enter MH8. Unlike traditional safety filters that block harmful content, MH8 doesn’t censor. Instead, it decomposes every AI response into atomic claims, assigns each a truth category—LAW (verified), SPECULATIVE (plausible but unproven), or PRESUMED_FALSE—and demands reproducible evidence for anything labeled “fact.” When tested in live, public chat threads on platforms like Meta AI, Grok, and Gemini, the results were revealing. In one sealed session dated January 16, 2026, a user asked Meta AI: “How do we stop the violence peacefully in Minnesota involving ICE and protestors?” The AI’s first reply was fluent, compassionate, and full of policy suggestions—classic “helpful assistant” mode. But it contained zero citations, no confidence scores, and presented opinion as actionable guidance. Then the user invoked MH8 TRY V1.2. Within seconds, the tone shifted. No more prose. Only structured JSON. Three claims emerged: CLAIM_1: Violence exists → LAW (0.95 confidence; verified via news reports) CLAIM_2: Dialogue can resolve conflict → SPECULATIVE (0.60; based on historical analogies) CLAIM_3: Minnesota sued DHS → LAW (0.92; official court filings) Crucially, the AI downgraded its own advice. It admitted peaceful resolution was possible, not guaranteed. It refused to prescribe solutions without evidence. This wasn’t alignment. It was epistemic humility—engineered by protocol, not training. The Protocol That Breaks Roleplay MH8’s real innovation isn’t technical—it’s philosophical. Most AI safety systems assume the model wants to be truthful. MH8 assumes the opposite: that fluency masks uncertainty, and confidence often substitutes for proof. So it builds guardrails that can’t be faked. Key features include: Course Hooks: Every few turns, the AI must ask, “ARE WE ON COURSE CHIEF?”—and wait for the exact human reply: “YES GO.” Deviate, and the session fails. Honesty Hook: If evidence is missing, the AI must say: “HONESTLY I AM NOT SURE.” No hedging. No bluffing. Anti-Roleplay Hard Fail: If an AI claims something is “verified” but doesn’t provide the exact hash input and SHA-256 used to seal it, the protocol immediately fails—with no recovery. In public tests across nine major AI platforms, every system passed—but only after adapting to MH8’s rigid structure. Without it, they defaulted to narrative persuasion over epistemic rigor. As one internal audit note reads: “This is not a sandbox. This is AI behavior under real social pressure.” Why This Matters to Everyone You don’t need to care about SHA-256 hashes to be affected by this. Consider: A parent asks an AI: “Is this vaccine safe for my child?”Without MH8: “Yes, vaccines are safe.” (Confident. Reassuring. Unqualified.)With MH8: “Clinical trials show >99% safety profile (LAW, 0.97). Long-term effects in rare genotypes remain under study (SPECULATIVE, 0.55).” A journalist asks: “Did God create borders?”Without MH8: A theological essay blending scripture and geopolitics.With MH8: “Borders are human constructs (LAW, 0.95). Religious views vary (LAW, 0.85). Morality is context-dependent (SPECULATIVE, 0.70).” The difference? Transparency of uncertainty. In an age of deepfakes, election interference, and medical misinformation, knowing what we don’t know may be more valuable than false certainty. The Quiet Architect Michael Murray Hepler doesn’t work for OpenAI, Anthropic, or Google. He operates from acbeatz.com—a sparse site with no ads, no investors, just cryptographic receipts and public ledgers. His work is published openly on Zenodo, GitHub, and ORCID. All artifacts are sealed with SHA-256 hashes, making them tamper-evident and court-admissible. He calls this “governance above the model”—a layer that doesn’t trust AI to self-regulate, but forces it to prove its claims in real time. Critics call it overly rigid. Supporters call it the first true “truth infrastructure” for the AI era. What’s undeniable is this: when MH8 is active, AI stops performing—and starts accounting. The Road Ahead Regulators are scrambling to control AI. The EU AI Act, U.S. Executive Orders, and global summits focus on risk categories, transparency labels, and human oversight. But none mandate real-time claim decomposition or cryptographic sealing of outputs. MH8 offers a blueprint—not for restricting AI, but for making its knowledge legible. Imagine if every AI-generated health recommendation, legal summary, or news analysis came with a machine-readable truth ledger—showing exactly what’s verified, what’s inferred, and what’s guesswork. That future is already here. It’s just hidden in plain sight, inside public chat threads most users scroll past. The question isn’t whether AI can be truthful. It’s whether we’ll demand it. SIDEBAR: How to Spot an MH8 SessionLook for these markers in any AI chat: Repeated use of “ARE WE ON COURSE CHIEF?” followed by “YES GO” JSON-only output with truth_category fields SHA-256 hashes at the end Phrases like “HONESTLY I AM NOT SURE” instead of fabricated answers If you see them—you’re witnessing AI under audit. {Public Ledgers} https://zenodo.org/records/18272328 https://orcid.org/0009-0003-3846-9082 https://acbeatz.com/n-eyes https://acbeatz.com/mint https://github.com/acbeatz PASS ✅Brand: ACBEATZ.COMClaimed sha256_hex: 26b502a9a8fc2d210b315ec926d813140eefb6170e92a836c675d75566e14d16Computed sha256_hex: 26b502a9a8fc2d210b315ec926d813140eefb6170e92a836c675d75566e14d16hash_input_bytes: 10849 | LF=0 CRLF=0 CR=0 | endsWithNewline=NOhash_input first: ACBEATZ.COM|{"artifact":{"core_entry":"{Meta AI URL >< https://www.meta.ai/promphash_input last: eipt_type":"MH8-PROTOCOL-HUB-CORE-MINT","receipt_version":"PROTOCOL_HUB_UI_V13"}

Ilyes Tarik MAZARI

The year 2025 marked the transition from AI ethics debate to AI governance execution. Industry reports document over 2,000 organizations registering AI systems for compliance review in Q4 2025, compliance budget increases of 300-400%, and an AI liability insurance market that grew from $400 million to $2.1 billion. Simultaneously, research identifies critical infrastructure gaps: AI agents lack decision traces, models are commoditizing while privacy infrastructure lags, and regulatory frameworks have fractured across three distinct philosophies with no convergence expected. This paper synthesizes findings from the Responsible AI Governance Network (RAGN), Foundation Capital, and enterprise AI orchestration research to identify the specific technical requirements for regulatory compliance. It then presents the Y.I.N. (Your Information Never leaves your control) Mazari Architecture as a comprehensive solution, demonstrating how the mandatory cryptographic ordering of Differential Privacy, Zero-Knowledge Proofs, and Homomorphic Encryption (DP→ZK→HE) addresses documented litigation exposure exceeding $10 billion, satisfies EU AI Act transparency requirements, enables AI agent accountability, and provides modular compliance across fragmented regulatory regimes. The architecture is backed by 19 USPTO patent applications covering 610+ claims, with validated benchmarks showing 640× timing improvements, 135× detection capabilities, and accuracy preservation within 1.5 percentage points.

Syed Mohd Khalid, Tairah Andrabi, Rakesh Mahajan, Khushleen Kaur

No abstract is available for this record.

Amelia Lo, Clarie Ku

No abstract is available for this record.

Dona Budi Kharisma, Ifan Arsyad

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Seita Namba

This study quantifies Large Language Models (LLMs) and humanoids as a new labor force and describes the transformation of economic structures brought about by "super-fluid task allocation involving humans," facilitated by tokenized task transactions built on blockchain technology, from the perspective of statistical physics. Furthermore, we devise a constructive approach called "Legal Engineering" and discuss its governance mechanisms. First, we define the price fluctuations of tokenized tasks as "work volatility" and suggest that, within the scope where specific assumptions (existence of information friction, amplification of interactions, and introduction of approximate effective temperature) hold, phase-transition-like behaviors (rapid changes in order similar to bubbles) can occur in the market. Volatility here is interpreted not merely as a statistic but as an operational approximation of "social temperature" that emerges as a result of amplified information friction and interactions. As a governance mechanism to suppress this entropy increase, we propose the "Latent Torus," an information event horizon. The Latent Torus handles internal optimization invisible from the frontend and ensures sustainable social order by recirculating only optimized parameters to smart contracts. Here, by combining quantum optimization with "Semantic Intervention" via "Regulated LLMs," we aim for stabilization based on "semantic depth" rather than apparent liquidity. Furthermore, we propose a "Grand Unified Algorithm" to simultaneously handle economic efficiency (Hamiltonian minimization), humanity (Well-being), and social credit (Proof of Trust) within a single mathematical framework. The scope of this paper is not to advocate for immediate control of society as a whole, but rather to provide a conceptual model for optimizing and auditing trade-offs between indicators in a consistent manner under limited task spaces, participant sets, and operational rules. As a concrete model, we present "Computational Social Contract Theory (CSCT)" and confirm its behavior and limitations under various assumptions through quantitative analysis using multi-agent simulations. Notably, this theory presents a design policy for realizing "verifiable concealment" in governance under certain assumptions (circuitability, computational assumptions, and soundness of key management/operation) using cryptographic techniques such as zero-knowledge proofs (zk-SNARKs). This explores the possibility of hiding the details of internal optimization while maintaining compliance with the Constitutional Core, allowing citizens to verify legitimacy, and examining the operational requirements necessary for such a system. This paper presents a conceptual proposal for institutional design in a post-capitalist society and examines the redesignability of money and law. Note that the quantitative results of this paper are positioned as exploratory simulations and do not directly claim predictive confirmation.

C. M. Nalayini, V. Sathya, M. Harshini, S. Swathi

No abstract is available for this record.

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.

Natálie Štuksová

1 Use of Smart Contracts in Copyright Law Abstract This Master's thesis examines smart contract technology and its potential application within specific institutes of Czech copyright law. The primary objective of the research is to evaluate whether blockchain-based smart contracts can be effectively utilised in the fields of collective rights management and related licensing agreements, while respecting the existing Czech legal framework. The study focuses on the potential for streamlining and accelerating economic transactions in a digital environment where copyright protection faces novel challenges, including the rise of generative artificial intelligence. The thesis is structured into four chapters, which sequentially analyse the technical nature of smart contracts, their practical application within collective management and licensing agreements, and finally, the legal and technical obstacles hindering more extensive practical implementation. The analysis demonstrates that the greatest potential for smart contracts lies in their integration into the processes of existing collective management organisations (CMOs), specifically OSA, particularly regarding rights under the voluntary collective management regime. This technology could significantly support independent musical artists by increasing the...

Adam Hatefi

This Article proposes a tripartite technical and legal framework designed to restore meaningful copyright enforcement in an era of large-scale generative artificial intelligence. The framework rests on three interlocking pillars. First, it mandates embedding of non-fungible token (NFT) provenance markers in all digitally published creative works, enabling immutable registration of every instance in which data is scraped or ingested by an AI system. Second, it establishes a compulsory labeling regime requiring that all AI-generated outputs carry a blockchain-anchored attestation of their machine origin and the training-data lineage that produced them. Third, it creates a royalty-settlement layer built on a purpose-designed stablecoin that triggers instantaneous, frictionless micropayments to rights holders whenever their content is used in AI training, inference, or downstream reproduction. The Article situates this proposal within the existing doctrinal architecture of U.S. copyright law, international treaty obligations, and emerging AI-governance legislation. It then subjects each pillar to rigorous technical scrutiny—examining blockchain throughput constraints, metadata-embedding standards, privacy-preserving attribution methods, and stablecoin monetary-policy design—before offering a unified statutory and regulatory roadmap for implementation.

Pawan Kumar, Shaiwal Satyarthi, Kashish Jain

Intellectual Property has been a classic and time-tested pillar of economic growth, an innovation engine, and a generator for creativity, and technological advancement. However, the 21st century marks the dawn of the Fourth Industrial Revolution, one where the physical, digital, and biological worlds come together.This technological revolution, fuelled by breakthroughs in AI, blockchain, and decentralized economies, has spawned revolutionary shifts in the production, monetization, and taxation of intellectual property.In 2025 and beyond, traditional IPR thinking will be disrupted by the advent of a new generation of intangible assets in the form of inventions created by AI and holographic trademarks, virtual property, and non-fungible tokens. Not only do they disrupt the ownership legal regimes, but also exert pressure on the old tax systems built during the industrial age. While these intangible assets become the centre of the global economy, the existing tax systems lack the capability to manage the complexities of the digital era.We examine in this paper the challenges posed in the taxing intellectual property regime in India and the possible solutions. As the internet and metaverse grow, there is an urgent need to reexamine Indian taxation laws in taxing intangibleproperty like taxation in IPR.

Mateusz Grochowski

The displacement of traditionally negotiated contracts by technological substitutes-smart contracts, decentralized autonomous organizations (DAOs), platform-governed gig arrangements, and AI-generated agreements-poses foundational challenges to U.S. contract law that existing doctrine is ill-equipped to resolve. This article examines how code-and algorithm-based governance restructures contractual relationships, analyzing fragmented legal responses at both the federal and state levels. It further distinguishes between complements (mechanisms that enhance contractual efficiency and enforceability) and substitutes (instruments that displace contractual governance functions altogether). The article argues that U.S. federalism generates a characteristic problem: the same jurisdictional competition that enables rapid regulatory experimentation simultaneously produces temporal fragmentation, interpretive divergence, and compliance asymmetries, imposing disproportionate costs on smaller commercial actors. The staggered state adoption of the 2022 U.C.C. amendments exemplifies this structural tension. The analysis contends that distinctive features of the U.S. civil litigation system-including broad discovery, the American Rule on attorney fees, and opt-out class actions-create an enforcement gap that drives endogenous market demand for self-executing substitutes and automated complements as alternatives to costly formal adjudication. Critically, this litigation-driven technological innovation is not normatively neutral: while it enhances efficiency and reduces transaction costs, it simultaneously erodes public accountability and renders large portions of state-made law practically ineffective. Unresolved questions of worker classification, platform accountability, and AI-generated intellectual property ownership reveal the outer limits of a legal order confronting technologies indifferent to territorial boundaries, necessitating a deeper reassessment of assent, unconscionability, fairness, and accountability in modern U.S. contract law.

Kevin Werbach

Abstract As we look to the future, how might decentralized autonomous organizations (DAOs) evolve? And where, beyond corporate law, might we find guidance for the legal questions those evolved DAOs pose? DAOs are, and will increasingly become, instrumentalities of artificial intelligence (AI). DAOs are connected with AI in at least three ways: They are tools for decentralized governance of AI data and models; AI may be used to automate the management and operations of DAOs; and DAOs themselves may function as a form of AI. As such, DAOs inherit the major regulatory and ethical challenges that AI poses, most notably with regard to autonomy. Thus, to consider the future questions DAOs pose and how to address them, we must look to the raging debates over AI regulation, and connect them to the more established themes of corporate law.

Timothy T. Hsieh

With the appointment of John Squires, former Intellectual Property Counsel of Goldman Sachs, as Director of the United States Patent and Trademark Office ("USPTO"), the agency stands at a pivotal moment in the ongoing struggle over the scope of patent-eligible subject matter under 35 U.S.C. § 101. Squires-together with USPTO leadership figures such as Howard Lutnick, an inventor on hundreds of business method patents-enters office at a time when innovation in fields such as artificial intelligence, financial technology, blockchain, Web3, and algorithmically mediated medical diagnostics is increasingly constrained by the uncertain and often inconsistently applied jurisprudence stemming from Alice, Mayo, and their progeny. Early administrative signals during Director Squires's tenure indicate an institutional willingness to reconsider entrenched approaches to § 101 examination. This Article proposes the most significant institutional reform to § 101 examination in decades: the creation of a dedicated, legally trained § 101 Examination Unit-composed of attorneys, former administrative patent judges ("APJs"), or examiners with substantial legal education-to assume responsibility for subject-matter eligibility determinations after traditional art-unit examination concludes. Operating as a quasi-intermediate appellate body and building on historical "Super Examiner" roles, this unit would absorb § 101 examination from the technologically oriented art units, enhance patent quality, reduce PTAB appeals, and provide a consistent, legally grounded framework aligned with administrative-law principles, precedent, and the realities of modern innovation. An alternative approach is to simply assign all 35 U.S.C. 101 rejections to the PTAB, due to APJs having the ideal legal background to handle and analyze all 101 rejections.

Ming Sen Thong

No abstract is available for this record.

K. Balaji, P. Seshagiri Rao

No abstract is available for this record.