The study applies a qualitative analytical approach utilizing a unique methodological framework: content analysis of global forecasting reports, algorithmic monitoring of social media engagement and comparative benchmarking of material technological specifications. Methods of morphological, colorimetric and semiotic analysis were utilized to identify key aesthetic and technological dominants. The research revealed a fundamental âaesthetic polarizationâ in 2025: the coexistence of âPhygitalâ aesthetics (metallics, 3D abstraction, neural network textures) and âRadical naturalnessâ (biomimicry, tactile surfaces). The concept of âarchitectural morphologyâ is introduced and substantiated, where the nail shape is conceptualized as an ergonomic structure with a compensatory function for anatomical correction. It is established that modern nail art requires the implementation of algorithmic design principles, including the Golden Ratio rule and specific colorimetric formulas (60-30-10), to achieve compositional integrity. The further development trajectory of the industry lies in the synergy of artistic modeling, digital services (AR fitting) and biotechnologies (âsmartâ and regenerative coatings). The work establishes a theoretical basis for elevating professional standards within the nail industry References 1. Belk, R. W. (2013). The extended self in a digital world. Journal of Consumer Research, 40(3), 477-500. 2. Kataila, Natalia. (2021). "Digital Fashion" on Its Way from Niche to the New Norm. 3. Kapferer, Jean-NoĂ«l & Michaut, Anne. (2015). Luxury and sustainability: a common future? The match depends on how consumers define luxury. Luxury Research J.. 1. 3. 10.1504/LRJ.2015.069828. 4. Hill, S. E., Rodeheffer, C. D., Griskevicius, V., Durante, K., & White, A. E. (2012). Boosting beauty in an economic decline: mating, spending, and the lipstick effect. Journal of personality and social psychology, 103(2), 275â291. https://doi.org/10.1037/a0028657 5. Lochhead, Robert. (2007). The Role of Polymers in Cosmetics: Recent Trends. ACS Symposium Series. 961. 3-56. 10.1021/bk-2007-0961.ch001. 6. Dorschel, Robert & Hermans, Anne-Mette. (2025). Body, beauty, enrichment: Theorizing the rise of the cosmetic industry through Boltanski and Esquerre's framework of enrichment. Journal of Cultural Economy. 1-17. 10.1080/17530350.2025.2478859. 7. Bhardwaj, Vertica. (2010). Fast fashion: Response to changes in the fashion industry. The International Review of Retail. Distribution and Consumer Research. 165-173. 10.1080/09593960903498300. 8. Goffman, E. (2021). The Presentation of Self in Everyday Life (Revisited ed.). Anchor Books. 9. Kim, E., Fiore, A. M., & Kim, H. (2021). Fashion trends: Analysis and forecasting (3rd ed.). Berg Publishers. 10. Draelos, Z. D. (2024). Cosmetic Dermatology: Products and Procedures (3rd ed.). Wiley-Blackwell. 11. Baran, R., & Maibach, H. I. (2019). Textbook of Nail Diseases: Diagnosis, Therapy, and Surgery (5th ed.). CRC Press. 12. Scher, R. K., & Daniel, C. R. (2005). Nails: Diagnosis, Therapy, Surgery. Elsevier Health Sciences. 13. Rieder, E. A., & Tosti, A. (2016). Cosmetically Induced Disorders of the Nail with Update on Contemporary Nail Manicures. The Journal of clinical and aesthetic dermatology, 9(4), 39â44. 14. de Berker D. (2013). Nail anatomy. Clinics in dermatology, 31(5), 509â515. https://doi.org/10.1016/j.clindermatol.2013.06.006 15. Elliot, A. J., & Maier, M. A. (2014). Color psychology: effects of perceiving color on psychological functioning in humans. Annual review of psychology, 65, 95â120. https://doi.org/10.1146/annurev-psych-010213-115035 16. Labrecque, L. I., & Milne, G. R. (2012). Exciting red and competent blue: The importance of color in marketing. Journal of the Academy of Marketing Science, 40(6), 711-727. 17. Joy, Annamma & Zhu, Ying & Peña-Moreno, Camilo & Brouard, Myriam. (2022). Digital future of luxury brands: Metaverse, digital fashion, and nonâfungible tokens. Strategic Change. 31. 337-343. 10.1002/jsc.2502. 18. Fraser, T., & Banks, A. (2004). Designerâs Color Manual: The Complete Guide to Color Theory and Application. Chronicle Books. 19. Pazda, Adam & Elliot, Andrew & Greitemeyer, Tobias. (2012). Sexy red: Perceived sexual receptivity mediates the red-attraction relation in men viewing woman. Journal of Experimental Social Psychology. 48. 787â790. 10.1016/j.jesp.2011.12.009. 20. Mezger, T. G. (2020). The Rheology Handbook: For those with practical tasks in rheology and viscometry (5th ed.). Vincentz Network. 21. Chevreul, M. E. (2021). The Principles of Harmony and Contrast of Colors and Their Applications to the Arts (Reprint ed.). Schiffer Publishing. (Original work published 1989). 22. Fechner, G. T. (2021). Vorschule der Aesthetik (Propaedeutics of Aesthetics) (Modern Translation). Breitkopf & HĂ€rtel. (Original work published 1876).
Samar Alsulaimani, Ming Zhao, Farookh Khadeer Hussain
âą Innovative Fractional Ownership Framework: The Fractional Digital Asset Ownership (FDAO) model uses fractional NFTs (FNFTs) to facilitate the co-ownership of digital assets, focusing on software code. âą Addressing Ownership Management Challenges: Building on FNFT and blockchain technology, this study proposes an intelligent solution for fractional digital asset ownership that ensures the accurate tracking of ownership rights through the integration of FNFTs with blockchain technology. âą Practical Prototype Development: This study demonstrates the FDAO frameworkâs capability to securely and transparently manage handling digital asset transactions using FNFTs and smart contracts implemented through Remix and OpenZeppelin. âą Empirical Evaluation of FNFT Application: This research examines the effectiveness of FNFT frameworks in supporting fractional ownership, highlighting their potential for real-world digital asset applications. âą Market Accessibility and Inclusivity: By enabling fractional ownership, the FDAO model increases accessibility to digital assets and supports ownership democratisation. âą Identification of Limitations and Future Directions: The study discusses the challenges related to regulatory compliance, scalability, and costs associated with FNFTs and other blockchain platforms and outlines compliance strategies that may support a broad range of applications. A new generation of digital assets is being managed using blockchain technology and non-fungible tokens (NFTs), which introduce novel opportunities for verifying ownership rights and establishing provenance. This paper presents an innovative framework called Fractional Digital Asset Ownership (FDAO), which aims to create NFTs for digital artifacts, such as software code, and extend their functionality through fractionalized NFTs (FNFT). Leveraging the Model-View-Controller (MVC) design pattern, FDAO enables effective co-ownership tracking across the lifecycle of digital assets, providing a structured and efficient mechanism for defining and managing co-ownership. A system prototype has been developed and tested in an integrated development environment (IDE) using decentralised applications (DApps) and smart contracts. Unlike existing NFT-based models, FDAO incorporates an intelligent, automated fractionalization and verification mechanism that combines the ERC-1155 and ERC-20 standards to enhance co-ownership management and scalability. This integration addresses the critical challenges related to transparency, security, and lifecycle management in digital asset co-ownership. The prototype, implemented using Remix and OpenZeppelin, demonstrates how FDAO enables secure, transparent, and efficient transfer and management of digital assets. By integrating FNFT functionality with smart contracts, the framework provides a robust, scalable, and intelligent method for managing digital assets. It also maintains transparency and trust throughout the asset lifecycle.
Patrick Spiesberger, Nils Henrik Beyer, Hannes Hartenstein
Ethereum's ideals of decentralization and censorship resistance are undermined in practice, motivating ongoing efforts to reestablish these properties. Existing proposals for fairness mechanisms depend on the assumption that a sufficient fraction of block proposers adhere to Ethereum's protocols as intended. We refer to such proposers as altruistic, as this behavior may come at the cost of reduced revenue. Prior analyses indicate that a consistent share of 91 percent of proposers delegate block construction to centralized services, effectively signing externally constructed blocks blindly, and are thus not considered altruistic. To assess whether the remaining 9 percent of proposers genuinely exhibit altruistic behavior, we conducted an empirical analysis and found that an additional 6.1 percent also interact with such external services. Further, we found that less than 1.4 percent of proposers consistently acted in accordance with Ethereum's decentralization and censorship resistance objectives. These findings suggest that relying solely on the mere presence of altruistic proposers is insufficient to ensure that proposed fairness mechanisms reestablish Ethereum's ideals, highlighting the need for additional incentive- or penalty-based mechanisms.
Dr. A. Radhika, D. Avinash, D. Sowjanya, K. Karthik · 5 authors
The increasing use of digital communication has made it essential to maintain the confidentiality, integrity, and authenticity of sensitive information. Conventional image steganographic methods offer data hiding in digital images, but they fail to offer effective tamper proofing and secure ownership verification. To overcome these issues, this paper presents a Blockchain-Integrated Secure Image Steganography system using IPFS and Ethereum. In the proposed system, secret data is hidden within digital images using a Least Significant Bit (LSB) image steganographic method developed in Python. The stego images are then stored in the Inter Planetary File System (IPFS) for efficient and decentralized data storage. To ensure data integrity and secure access, the cryptographic hash values of the stego images and their corresponding IPFS Content Identifiers (CIDs) are securely stored on the Ethereum blockchain using smart contracts. The use of blockchain technology provides immutability, transparency, and tamper resistance, and IPFS provides decentralized storage without depending on centralized storage servers. The proposed system is validated to offer high image quality with negligible distortion and robust data security and traceability. This system is applicable for secure data sharing in confidential communication, digital forensics, and secure document transfer.
Open access
Advanced Steganography and Watermarking Techniques
Blockchain technology has evolved incredibly into various domains other than cryptocurrencies such as healthcare, genomics application, agriculture, government schemes, land asset distribution, DeFi, IoT, supply chain management due to its decentralized and secured nature. Consensus mechanism in blockchain networks serves as the backbone to ensure data integrity, provenance, immutability and security. Traditional consensus mechanism faces many challenges like utilization of high energy or carbon, excessive computational resources, staking of cryptocurrency, high reputation of nodes, maximum votes received, scalability and security issues. To tackle this concerns many researchers has proposed solutions and given a comparative analysis of the performance of these algorithms. This paper gives the survey reviews of the consensus mechanism used so far with a comparative analysis on the performance metrics like scalability, latency, and throughput, degree of decentralization, energy and resources efficiency etc. We have divided the consensus algorithms based on two categories i.e Proof based and Acquiescence based. The study highlights critical trade-offs among scalability, energy efficiency, decentralization, fault tolerance, and security resilience. Furthermore, this paper sheds the light on recent innovations addressing mitigation strategies like sharding, off-chain solutions, checkpoint mechanism, and integration of machine learning for anomaly detection, prediction of attack vectors. By systematically comparing consensus protocols and identifying open research challenges, this review aims to provide researchers and practitioners with a clear understanding of current consensus landscapes and provide valuable guidance to the selection and design of suitable mechanisms for next-generation blockchain systems.
Patrick Spiesberger, Nils Henrik Beyer, Hannes Hartenstein
Ethereum's ideal of censorship resistance, together with related fairness properties, is undermined in practice, motivating fairness mechanisms that aim to restore these properties. Several of these mechanisms hand control over block contents to a committee of proposers under a 1-of-n honest assumption: at least one committee member complies with the mechanism even when deviating would increase personal revenue. We refer to such proposers as altruistic. Yet prior work shows that roughly 91 percent of blocks are constructed by centralized block-building services that demonstrably take user-adverse actions for financial gain; the responsible proposers sign these blocks blindly, without any means of intervention. A common reading of this figure is that 9 percent of proposers forgo these gains and act altruistically. Our empirical analysis of the full year 2025 shows that this share is far smaller: at most 1.55 percent of proposers can plausibly be regarded as altruistic, whereas the remaining 98.45 percent of proposers exhibit observable non-altruistic behavior. We interpret 1.55 percent as an upper bound on the prevalence of altruistic proposers. These results imply that committee-based fairness mechanisms that rely on altruistic members would require substantially larger committees than currently proposed. This raises concerns about their practical viability and motivates mechanisms in which fair behavior is the rational choice.
Justin Wang, Andreas Bigger, Xiaohai Xu, Jiahao Lin · 8 authors
Smart contracts on public blockchains now manage large amounts of value, and vulnerabilities in these systems can lead to substantial losses. As AI agents become more capable at reading, writing, and running code, it is natural to ask how well they can already navigate this landscape, both in ways that improve security and in ways that might increase risk. We introduce EVMbench, an evaluation that measures the ability of agents to detect, patch, and exploit smart contract vulnerabilities. EVMbench draws on 117 curated vulnerabilities from 40 repositories and, in the most realistic setting, uses programmatic grading based on tests and blockchain state under a local Ethereum execution environment. We evaluate a range of frontier agents and find that they are capable of discovering and exploiting vulnerabilities end-to-end against live blockchain instances. We release code, tasks, and tooling to support continued measurement of these capabilities and future work on security.
In blockchain ecosystems, maintaining transparency and privacy has become an ethical dilemma. This is because, while certain specific information of the user is shared to ensure transparency of transactions across networks, such information could be detrimental to the user, as there is a possibility of it being tampered with. For instance, in the Catalyst voting process in Cardano, users can still see the amount of ADA tokens being held by other users, which can influence their voting options, especially when large ADA holders vote in support of certain ideas or proposals. To discourage such challenges as voter manipulation and vote buying, this study proposed the implementation of zero-knowledge proof (ZKP) in blockchain ecosystems to enhance the transparency of the catalyst voting process and enhance efficiency and speed of result release. Using survey questionnaire and a multivocal literature review, this study was able to proof that ZKP cannot only be applied in the catalyst voting process to enhance its transparency, but also addressed potential challenges to its applications such as scalability, encourage trust and fairness of the voting system, and improve voter participation due to its user-friendliness. Mathematical models emphasize scaled voting as optimal for balancing inclusion and plutocratic control.
When individual robots have limited sensing capabilities or insufficient fault tolerance, it becomes necessary for multiple robots to form teams during exploration, thereby increasing the collective observation range and reliability. Traditionally, swarm formation has often been managed by a central controller; however, from the perspectives of robustness and flexibility, it is preferable for the swarm to operate autonomously even in the absence of centralized control. In addition, the determination of exploration targets for each team is crucial for efficient exploration in such multi-team exploration scenarios. This study therefore proposes an exploration method that combines (1) an algorithm for self-organization, enabling the autonomous and dynamic formation of multiple teams, and (2) an algorithm that allows each team to autonomously determine its next exploration target (destination). In particular, for (2), this study explores a novel strategy based on large language models (LLMs), while classical frontier-based methods and deep reinforcement learning approaches have been widely studied. The effectiveness of the proposed method was validated through simulations involving tens to hundreds of robots.
Traditional financial institutions face inefficiencies that can be addressed by distributed ledger technology. However, a primary barrier to adoption is the privacy concerns surrounding publicly available transaction data. Existing private protocols for distributed ledger that focus on the Ring-CT model are not suitable for adoption for financial institutions. We propose a post-quantum, lattice-based transaction scheme for encrypted ledgers which better aligns with institutions' requirements for confidentiality and audit-ability. The construction leverages various zero-knowledge proof techniques, and introduces a new method for equating two commitment messages, without the capability to open one of the commitment during the re-commitment. Subsequently, we build a publicly verifiable transaction scheme that is efficient for single or multi-assets, by introducing a new compact range-proof. We then provide a security analysis of it. The techniques used and the proofs constructed could be of independent interest.
We study the deployment performance of machine learning based enforcement systems used in cryptocurrency anti money laundering (AML). Using forward looking and rolling evaluations on Bitcoin transaction data, we show that strong static classification metrics substantially overstate real world regulatory effectiveness. Temporal nonstationarity induces pronounced instability in cost sensitive enforcement thresholds, generating large and persistent excess regulatory losses relative to dynamically optimal benchmarks. The core failure arises from miscalibration of decision rules rather than from declining predictive accuracy per se. These findings underscore the fragility of fixed AML enforcement policies in evolving digital asset markets and motivate loss-based evaluation frameworks for regulatory oversight.
The rapid digitalization of wealth in the form of cryptocurrency and virtual assets has dramatically transformed the results of the matrimonial conflicts and alimony payments. With the gr owing adoption of decentralized and pseudonymous digital assets as constituents of individual financial portfolios, family courts face new issues in their classification, disclosure, valuation, and enforcement. The legal issues discussed in this paper include the legal complications of cryptocurrency as marital property, the risk of concealing assets through blockchain anonymity, and challenges of valuation, associated with the excessive price volatility, tax exposure, enforcement challenges linked to the control of private keys, and jurisdictional challenges across borders. It also examines new legal and forensic systems and contractual protection mechanisms that are intended to manage these issues. The paper claims that although the classical tenets of equitable allocation and full disclosure are still underpinning, the concept of clarity in the law and judicial flexibility is needed to provide equal justice, openness, and enforceability of the divorce process concerning cryptocurrency and virtual possessions.
Zero-knowledge proof security rests on cryptographic reductions: breaking a ZK scheme requires breaking an underlying hard problem. We introduce an independent, complementary security analysis based on the Structural Action Principle. We extend the discrete action functional S[psi] = sum_t lambda(s_t) from Boolean CDCL trajectories to algebraic constraint systems over finite fields F_p, defining an Algebraic Structural Action with density functions that recover Groebner basis complexity, Polynomial Calculus proof size, algebraic degree growth, and elimination ordering as mechanical analogues. We prove a non-circular lower bound for preimage search in substitution-permutation network (SPN) hash functions: for a k-round SPN with S-box degree alpha and state width t, the preimage search system is a square polynomial system of k*t degree-alpha equations in k*t variables. Under the semi-regularity assumption (standard in algebraic cryptanalysis, empirically verifiable, and independent of any cryptographic security conjecture), the solving degree d_reg is determined by the Hilbert series H(z) = (1 - z^alpha)^{k*t}/(1-z)^{k*t}. We establish two action bounds: a peak bound S[psi] >= d_reg (any trajectory must encounter degree d_reg), and a stronger cumulative bound S[psi] >= sum_{d=alpha}^{d_reg-1} h_d using the Hilbert function coefficients as density, which captures the total algebraic work rather than just the peak degree. For Poseidon (alpha=5, t=3, k=8): d_reg = 97 and the cumulative bound gives S[psi] >= 2^{56}. The result applies to ANY SPN hash function (Rescue, Griffin, Anemoi, MiMC) and provides a second line of defense for Behavior-Bound Signature (BBS) security, grounded in algebraic proof complexity rather than crypto- graphic hardness assumptions. Keywords: structural action principle, algebraic proof complexity, polynomial calculus, semi-regularity, Hilbert function, SPN hash functions, zero-knowledge security, behavior-bound signatures
The rapid rise in cryptocurrencies has created an investment environment marked by unprecedented levels of information volume, fragmentation, and volatility. While prior research has examined drivers of trust and adoption in crypto markets, far less is known about the psychological consequences of information overload on investor decision-making. This study addresses this gap through nineteen semi-structured interviews with individual cryptocurrency investors, analyzed using an inductive, manually conducted thematic approach. Findings reveal four interconnected dynamics: decision fatigue and paralysis, heuristic reliance on influencers and peers, emotional strain characterized by anxiety and fear of missing out (FOMO), and diverse coping strategies ranging from selective filtering to withdrawal. These results demonstrate that crypto investing is not only a financial process but also a cognitively and emotionally taxing experience. By linking investor narratives to broader theories of decision fatigue, bounded rationality, and consumer vulnerability, the study contributes to interdisciplinary debates in marketing, behavioral finance, and consumer psychology. Practically, the findings highlight the need for clearer communication strategies, supportive platform design, and financial education initiatives that help investors manage cognitive strain and decision fatigue. In a market where credibility is fluid and decisions are often made under conditions of overload, understanding the psychological dimensions of investment behavior is essential.
The city of Cluj-Napoca turned into the biggest real estate boom in Romania. Although wages have remained at the national average level by field of activity, the price of housing tends to take such a large scale that it exceeds the amount of real estate in many European countries and cities. The community of ordinary, honest and industrious people sees themselves excluded from their own city, suffering because of this price explosion which has an impact in all social spheres. The explanation that the price level is due to the large number of students and computer scientists is easy and convenient for the authorities who do not really have reactions, answers and solutions. KEYWORDS: accommodation, maximum profit, corruption, computer scientists, real estate, money laundering, indolence, incompetence, complicity, community suffering, emigration, solutions. J.E.L. Classifications: R31, R23, O18 1. ARGUMENT After December 1989 in Cluj-Napoca there were phenomena and facts prominently highlighted on the national socio-economic map: the Caritas pyramid megagame, the FNI scam guaranteed in the end by the CEC, the bankruptcy of the largest private Bank "Dacia Felix", the headquarters of two antagonistic national parties UDMR and PUNR and very important, in the long term, the expansion of "BabeÈ Bolyai" University which became the largest in the country, both in terms of number of students and as the number of sections. The transformation of the number of students into an economic, not only scientific, cultural and social argument, even without coverage on the labor market, induced the increase in the number of students at all universities. It is not easy to mention "all" universities! The six state universities have a large share: "BabeÈ Bolyai" University, Technical University, University of Medicine and Pharmacy, University of Agricultural Sciences and Veterinary Medicine, University of Art and Design, Academy of Music. Along with these, the legislation after 1989 allowed the establishment of private education - "Bogdan VodÄ" University (one of the first in the city), Dimitrie Cantemir University (centered in Bucharest, but with strong branches of Law and Economic Sciences in Cluj), "Sapientia" University focused on the Hungarian community, as well as "Partium" University in Oradea which has activity in Cluj as well, as well as other higher education institutions reorganized/disbanded over time, or with more limited or meteoric activity - "Avram Iancu", "Spiru Haret", "Phoenix", the Protestant Theological Institute and we do not claim to list exhaustively. It is certain that Cluj-Napoca has the highest density of students compared to the number of inhabitants in the country. These crowds of students, about 100 thousand with master's and doctoral students, in principle, were mainly charged tuition fees and all kinds of expenses were increased, based on the well-known principle of the price that appears as a result of the competition between demand and supply. There is a very high demand in Cluj, sometimes exorbitant, the solution, the most profitable and immediate, was just to increase the prices. Given that practically no dormitories were built after 1989, (only one in the Gheorghieni District, near "Economic Sciences" - FSEGA, but it is not entirely dedicated to students) among the prices that have exploded in Cluj, the shocking is that of rents and, logically, in the next steps, real estate prices. The explanation of the large number of students and IT specialists is the most convenient in excusing apathy or anti-crime inefficiency, but it is also necessary to analyze the hypothesis if part of the pressure on prices can come from financial flows associated with organized crime. 2. POSTULATED: ORGANIZED CRIME IS INTERESTED BY THE BIGGEST PROFIT The accommodation capacity in the state dormitories is approximately 14,000-15,000 places, and the students who do not get a place in the dorm, volens-nolens, enter a rental market where a level of 300-500 euros for a studio apartment excludes young people from disadvantaged backgrounds from Cluj university studies. Many of them would have deserved to perform in Cluj! It is estimated that approximately 65,000 students live in rented accommodation annually. Most students barely pay their rent and living expenses, very few can afford to enter the property market as buyers. There is, however, one category that influences the real estate market the most - IT specialists. They influence more because they have high salaries relative to the rest of the population. However, the infusion of students and the university environment determined the explosion of the crowd of IT-scientists in Cluj-Napoca, rightly considered a "Silicon Valley" of Eastern Europe. The estimate goes up to the existence of about 30,000 IT specialists in Cluj with a number of over a thousand active IT companies. All of these provide clues to the size of the rental market and the total value of real estate transactions. In 2025, Cluj county registered an approximate volume of 30,782 real estate transactions with an estimate of between 1.8 - 2.2 billion EUR annually (sources: ANCPI - National Real Estate Agency; Imobiliare.ro; Storia.ro s.a.). The rental market is more difficult to quantify, but it can be approximated by the number of residential units estimated to be in the rental circuit of at least 45-50 thousand units (apartments and rooms). Considering the data published in some specialized websites, Imobiliare.ro; Storia.ro, or of public institutions (City Hall of Cluj Napoca - floating population) we arrive at a total estimated annual value of approx. 300 million EUR. What happened in the USA during alcohol prohibition when alcohol smuggling produced a huge amount of black money? Who appeared on the market? In drugs, in human trafficking, in the smuggling of oil to Yugoslavia in the 90s, in the massive cutting of forests in countries that do not protect them, in prostitution, in gambling and betting, wherever, when the stake of a very large profit appears, even if it is illegal, who undoubtedly appears? Popular wisdom has an expression that captures the phenomenon: "Let it be, because frogs gather!" Is there a risk that part of the real estate market in Cluj or in Romania will be accessed, influenced or even controlled by organized crime? The clearest proof of the influence of organized crime is the huge number of homes sold that remain unoccupied! Between 18,000 and 24,000 housing units, depending on the information sources, in Cluj-Napoca alone. Thousands of apartments are bought for hoarding. Rising property prices coupled with very low interest rates offered by banks on savings have made buying an additional home an investment for anyone who can afford it. But it is also a classic method of money laundering where the goal is not the profit from the rent, but the legalization of the initial amount through subsequent resale. REAL ESTATE IS FAVORITE TO BE A "SAFE HAVEN" (SAFE REFUGE) FOR ILLICIT CAPITAL Although the presence of the IT sector and students would lead to the thought of a constant demand, especially in the conditions in which a salary recession in IT is foreseen (it actually took place), the hyperbolic evolution of real estate prices in Cluj cannot be justified. Practically, these real estate prices have been decoupled from the real purchasing power of the average salary, even if this "average", in Cluj, contains a lot of IT. Who does the disconnection? A working student, a programmer even with an above-average income is subject to the bank lending grids. When the price per square meter exceeds the threshold of 3000 euros/sq m, or in special areas/center, over 5000 euros/sq m, they become unaffordable for the middle class through mortgage credit. Everyone knows that high prices are supported with "cash", which highlights sources of financing external to the transparent banking system, specific to organized crime that needs to "clean" financial funds of dubious origin as quickly as possible. It's like a geometric law, a postulate, it's just like that, but even if it's like that, it's certainly not a proof on file, it's just an assumption. There are institutions that, based on some laws, will look for this evidence, being within their competence. Some authors on economic crime suggest that real estate markets in fast-growing cities may become vulnerable to the infiltration of capital from illicit activities (Unger, 2021). The real estate sector is recognized as a classic instrument for money laundering, including the profits from drug trafficking (FATF, 2019). An interesting work in the field is by a collective led by Klitgaard Robert "Corrupt Cities: Practical Guide to Institutional Reform". These specialists identify three main mechanisms: money laundering through real estate investments because real estate offers: high and relatively stable value; the possibility of justifying the origin of the funds; integration into the formal economy. capital reinvested from the drug market. According to the UN Office on Drugs and Crime (UNODC), the drug market generates hundreds of billions of USD annually globally (UNODC, 2023). Part of these funds are reinvested in: residential real estate; commercial premises; urban developments. In Europe, studies on cities such as Amsterdam or Barcelona have shown correlations between the underground economy and speculative real estate investments (Savona, 2020). the third mechanism refers to demand distortion. Is it the case of Cluj? preservation of value; anonymization of property; integration into the legal circuit. Thus, artificial demand can push prices above the level determined strictly by legitimate supply and demand. COMPETENT INSTITUTIONS, CASE STUDY AND THE THREAT NARCO TRAFFIC Combating the phenomenon would require the coordinated action of several institutions: Directorate for the Investigation of Organized Crime and Terrorism (DIICOT) National Anticorruption Directorate (DNA) National Office for the Prevention and Combating of Money Laundering (ONPCSB) National Fiscal Administration Authority (ANAF) General Inspectorate of the Romanian Police (IGPR) Law no. 656/2002 on the prevention and sanctioning of money laundering Law no. 143/2000 on preventing and combating drug trafficking and illicit drug consumption Criminal Code (art. 367 â organized criminal group) Examples of relevant files: Romania 2020 â DIICOT file on drug trafficking and money laundering through real estate purchases in Bucharest (DIICOT public release); 2022 â File regarding an organized criminal group involved in tax fraud and real estate investments (Bucharest Court of Appeal), 2023 â Case instituted by DIICOT regarding cocaine trafficking and property investments in the west of the country. Germany: Investigations coordinated by the Bundeskriminalamt (BKA) demonstrated the use of real estate for the recycling of profits from drug trafficking networks (BKA Report, 2021). Netherlands: The Financial Intelligence Unit (FIU Nederland) reported in 2022 the increase in suspicious transactions in the real estate sector in Amsterdam, associated with the drug economy. THE THREAT OF DRUG TRAFFICKING ON CLUJ. INCLUSIVE OF CLUJ REAL ESTATE Cluj-Napoca is a major university center, and the reports of the National Anti-Drug Agency indicate the existence of high consumption in the university environment (ANA, 2022). In economic theory, a city with: high consumption, logistical proximity, high purchasing power, can generate important financial flows in the underground economy. If these flows are reinvested in real estate, it results: additional pressure on demand; cash purchases; lack of price sensitivity. However, we note that no public data has been identified that accurately quantifies the weight of this phenomenon in the formation of prices in Cluj-Napoca. 6. CONCLUSIONS AND PROPOSALS It is well known that the upward spiral of real estate has a major negative impact on all components of social life. Institutions with competences in the field are expected to leave their mark more and contribute to the normalization of the perspectives of local communities, despite a lack of social reactivity typical of an increasingly aggressive, apathetic population, resigned to the idea that nothing can be done to improve living conditions. A lot can still be done, there are international anti-corruption models. Where there was political will, things got better, some negative phenomena were even eradicated, and some proposals can be extracted from those models: Extending the verification of the source of funds for transactions above a certain value threshold. Constantly checking the real prices from the real estate agencies with those declared at the notary chambers: Automatic interconnection ANAFâONPCSBâDIICOT. Complete public register of beneficial owners (in line with EU Directive 2018/843). Extended confiscation according to art. 112 Criminal Code. Romania is the country that in peacetime was condemned by pauperization, lack of perspective, systemic corruption to have the largest share of emigrant population in Europe, and of course with an unwanted leading place in the world, and all this took place in peacetime. By analogy, from the much-acclaimed "5-star city", the aberrant price spiral in Cluj-Napoca can produce similar, uncontrollable effects internally. Paraphrasing the legal admonition, we would conclude by warning, "Any silence can turn against us!" REFERENCES National Antidrug Agency (2022). National report on the drug situation in Romania. Balan, C. (2023). Urban economy and real estate market. ASE publishing house. Bundeskriminalamt (2021). Organized Crime Situation Report. Financial Action Task Force (2019). Money Laundering & Real Estate FIU Nederland (2022). Annual Report on Suspicious Transactions. Glaeser, E. (2011). Triumph of the City. Penguin Press. Klitgaard Robert s.a "Corrupt Cities: Practical Guide to Institutional Reform" Ed. Humanitas, Bucharest 2012 Marian Adrian Sorin, s.a THE STUDENT'S GUIDE, Mega Publishing House, Cluj-Napoca, 2016, Marian Adrian Sorin, "Why do Romanians emigrate?" Galaxia Gutenberg Publishing House, Cluj-Napoca, 2023, Marian Adrian s.a, Competences and milestones of training and cooperation in the public order and safety system Galaxia Gutenberg Publishing House, Cluj-Napoca, 2021 Savona, E. (2020). Organized Crime in European Cities. Springer. Unger, B. (2021). The Role of Real Estate in Money Laundering. Journal of Financial Crime. United Nations Office on Drugs and Crime (2023). World Drug Report. ***Law no. 656/2002 for the prevention and sanctioning of money laundering
This study investigates the relationship between public attention to the Sustainable Development Goals (SDGs) and cryptocurrency demand, specifically for Bitcoin (BTC) and Cardano (ADA). Given the environmental concerns associated with Proof-of-Work (PoW) and the sustainability benefits of Proof-of-Stake (PoS), we hypothesize that increased SDG attention leads to higher demand for green cryptocurrencies like Cardano and lower demand for non-green cryptocurrencies like Bitcoin. Using Ordinary Least Squares (OLS) regression and supervised machine learning algorithms, we analyze weekly cryptocurrency returns and Google Trends data from 2020 to 2025. The findings suggest that SDG attention has a statistically significant but weak negative impact on Bitcoin returns, while no significant effect is observed for Cardano. Machine learning models fail to predict cryptocurrency demand effectively. These results indicate that sustainability awareness alone is not a primary driver of cryptocurrency investment behavior.
Central Bank Digital Currency (CBDCs) are becoming a new digital financial tool aimed at financial inclusion, increased monetary stability, and improved efficiency of payment systems, as they are issued by central banks. One of the most important aspects is that the CBDC must offer secure offline payment methods to users, allowing them to retain cash-like access without violating Anti-Money Laundering and Counter-terrorism Financing (AML/CFT) rules. The offline CBDC ecosystems will provide financial inclusion, empower underserved communities, and ensure equitable access to digital payments, even in connectivity-poor remote locations. With the rapid growth of Internet of Things (IoT) devices in our everyday lives, they are capable of performing secure digital transactions. Integrating offline CBDC payment with IoT devices enables seamless, automated payment without internet connectivity. However, IoT devices face special challenges due to their resource-constrained nature. This makes it difficult to include features such as double-spending prevention, privacy preservation, low-computation operation, and digital identity management. The work proposes a privacy-preserving offline CBDC model with integrated secure elements (SEs), zero-knowledge proofs (ZKPs), and intermittent synchronisation to conduct offline payments on IoT hardware. The proposed model is based on recent improvements in offline CBDC prototypes, regulations and cryptographic design choices such as hybrid architecture that involves using combination of online and offline payment in IoT devices using secure hardware with lightweight zero-knowledge proof cryptographic algorithm.
This article examines the utilization of Distributed Ledger Technology (DLT) as a mechanism to address import customs tax evasion. The research employs a game-theoretic framework to examine the dynamics of tax evasion and assess the impact of blockchain on improving transparency, accountability, and compliance in customs administration. A systematic literature review process, adhering to PRISMA criteria, was utilized to gather and examine pertinent academic articles. The literature study examines critical subjects, such as the mechanisms of import tax evasion, the digital taxation framework, and the use of blockchain technology into tax systems. The study also examines the relevance of game theory in comprehending and addressing non-compliant behaviors among taxpayers. In the practical phase, we conducted a systematic review of a corpus exceeding 100 publications, obtained from three international research databases: Scopus, Taylor & Francis, and IEEE Xplore. Following the application of rigorous inclusion and exclusion criteria to guarantee relevance, a concentrated selection of research constituted the foundation for our study. This research underscores the capacity of DLT to transform conventional evasion tactics, reduce corruption, and improve institutional efficacy in customs operations. Insights are contextualized through a worldwide comparison and an examination of the Moroccan customs scene, offering concrete recommendations for utilizing blockchain to modernize customs operations.
This paper explores the paradigm shift from centralized, command-and-control systems to decentralized, knowledge-driven structures across economic, organizational, technological, and social domains. The inefficiencies and lack of innovation in centrally planned systems stem largely from informational constraintsâparticularly the inability to effectively gather, process, and utilize dispersed, local, and tacit knowledge. Decentralization enables autonomous agents to leverage their own knowledge, fostering experimentation, innovation, and adaptability. Through a series of examplesâincluding economic markets, firms, states, environmental systems, communications networks, and educational modelsâthe paper illustrates how decentralization replaces vertical, hierarchical communication with horizontal, networked interactions. The transition is characterized by the central authority relinquishing direct control in favor of setting rules of interaction, thereby mitigating principal-agent problems and enhancing system robustness. The analysis extends to social learning, contrasting passive, top-down education with active, dialogical learning, and highlights the importance of intellectual freedom and experimentation in organizations and societies. The overall conclusion is that successful decentralization depends on well-designed rules that maximize autonomy and spontaneous activity, consistent with the broader goal of compossible freedom for all agents.
The increasingly complex Web3 ecosystem and decentralized finance (DeFi) landscape demand ever higher levels of technical expertise and financial literacy from participants. The Intent-Centric paradigm in DeFi has thus emerged in response, which allows users to focus on their trading intents rather than the underlying execution details. However, existing approaches, including Typed-intent design and LLM-driven solver, trade off expressiveness, trust, privacy, and composability. We present OMNIINTENT, a language-runtime co-design that reconciles these requirements. OMNIINTENT introduces ICL, a domain-specific Intent-Centric Language for precise yet flexible specification of triggers, actions, and runtime constraints; a Trusted Execution Environment (TEE)-based compiler that compiles intents into signed, state-bound transactions inside an enclave; and an execution optimizer that constructs transaction dependency graphs for safe parallel batch submission and a mempool-aware feasibility checker that predicts execution outcomes. Our full-stack prototype processes diverse DeFi scenarios, achieving 89.6% intent coverage, up to 7.3x throughput speedup via parallel execution, and feasibility-prediction accuracy up to 99.2% with low latency.
Using on-chain Polygon data, we analyze Polymarket's 2024 U.S. Presidential Election market and develop a transaction-level accounting framework with two components: a volume decomposition that separates exchange-equivalent turnover from share minting and burning, and trader-level disagreement measures. Naive aggregation reports $958M of October Trump-market volume, compared with $391M under our decomposition. Market quality improved as arbitrage-deviation half-lives fell from hours to under a minute and Kyle's λ dropped from 0.53 to 0.01. During October's large-account episode, capital flowed into both sides simultaneously, consistent with heterogeneous-beliefs trading rather than one-sided manipulation. The framework generalizes to other tokenized prediction markets.
Time series forecasting enables early warning and has driven asset performance management from traditional planned maintenance to predictive maintenance. However, the lack of interpretability in forecasting methods undermines users' trust and complicates debugging for developers. Consequently, interpretable time-series forecasting has attracted increasing research attention. Nevertheless, existing methods suffer from several limitations, including insufficient modeling of temporal dependencies, lack of feature-level interpretability to support early warning, and difficulty in simultaneously achieving the accuracy and interpretability. This paper proposes the interpretable polynomial learning (IPL) method, which integrates interpretability into the model structure by explicitly modeling original features and their interactions of arbitrary order through polynomial representations. This design preserves temporal dependencies, provides feature-level interpretability, and offers a flexible trade-off between prediction accuracy and interpretability by adjusting the polynomial degree. We evaluate IPL on simulated and Bitcoin price data, showing that it achieves high prediction accuracy with superior interpretability compared with widely used explainability methods. Experiments on field-collected antenna data further demonstrate that IPL yields simpler and more efficient early warning mechanisms.