Varna Free University

This article examines vulnerability to counterfeit currency fraud in Bulgaria by assessing citizens’ competence in recognizing genuine banknotes of the national currency (BGN) prior to the introduction of euro banknotes in 2026. Counterfeit banknotes represent a form of economic crime in which individual victims’ losses are closely tied to their ability to authenticate cash in everyday transactions. Drawing on level-1 security features and guidelines of the Bulgarian National Bank, we developed a structured questionnaire to operationalize knowledge of key authenticity checks (hologram, intaglio printing, watermark, security thread, see-through register). The survey was administered online and on paper over a 20-day period (22 August–11 September 2025) and completed by 371 respondents from across the country. Using descriptive statistics tools, we identify three distinct groups: (i) highly competent respondents who reliably distinguish genuine from counterfeit banknotes; (ii) individuals with high self-reported confidence but inconsistent performance; and (iii) a particularly vulnerable group with low knowledge of security features, limited awareness of official guidance and low self-confidence. Vulnerability is significantly associated with lower education, residence in smaller settlements, lack of prior exposure to counterfeit banknotes and absence of contact with institutional information campaigns. The findings have direct implications for crime prevention and criminal justice policy: they provide an evidence base for targeted public awareness initiatives and risk-based allocation of resources aimed at protecting high-risk groups from currency-related fraud in the context of the monetary transition.

Digital transformation is central to circular economy (CE) strategies, yet the intersection between digital innovation and women's entrepreneurship remains underexplored. We examine how IoT, AI, blockchain, data analytics and platform technologies are represented in CE-oriented management research and assess the visibility of gender-inclusive and women entrepreneurship perspectives. We merged Scopus and Web of Science records (2015-2025), removed duplicates, screened for relevance, and mapped themes and networks using bibliometrix (R) and VOSviewer. Digital-CE scholarship was found to rise after 2018, dominated by smart manufacturing, circular supply chains, digital product passports and blockchain traceability. Four clusters emerged: digital circular manufacturing, circular business model innovation, waste and resource management, and policy-social aspects. Gender-related terms appear in only 1.35% of the corpus, revealing a gap between academic research and EU policy priorities for inclusive digital and circular transitions. We integrate a gender-inclusive lens and outline an agenda positioning women entrepreneurs as critical yet overlooked actors in digital circular ecosystems. As a bibliometric review, this study maps scholarly attention rather than the prevalence of women-led circular ventures. Beyond mapping, we advance the paper's primary contribution by proposing a governance-oriented synthesis that frames digital infrastructures as administrative mechanisms shaping who can participate in, benefit from, and influence digital circular ecosystems.

We compare classical and modern regression models for next-day cryptocurrency forecasting on 14 USD-denominated coins across three liquidity tiers from 2018 through 2025, and we use the resulting panel to formally test three pre-specified hypotheses. The features are a strictly past-only 28-element set; the evaluation uses expanding-window walk-forward cross-validation with nested hyperparameter tuning, stationary block-bootstrap 95% confidence intervals, and pairwise Diebold-Mariano tests. Methodologically, we derive a bias-variance bound that turns the 'no model beats the mean' observation from a null finding into a predicted outcome under weak-form market efficiency. Empirically, (H1) the threshold-effect interaction is not supported (slope -1.7 & times; 10-4, 95% CI [-4.8 & times; 10-4, +1.4 & times; 10-4], p = 0.25). (H2) Statistical loss minimisation is decoupled from risk-adjusted economic outcome: the cluster-bootstrapped 95% CI for the Spearman rank correlation between the within-ticker MAE rank and within-ticker post-cost Sharpe rank is [-0.39, +0.10] overall, lies *strictly below zero* on the mid-cap (CI [-0.71, -0.04]) and long-tail (CI [-0.26, -0.09]) tiers, and decisively rejects perfect alignment (rho = +1) on every tier. None of the seven (ticker, model) pairs with annualised Sharpe >= 0.5 has a hit rate significantly different from 0.5; high-Sharpe outcomes reflect return skew, not directional skill-formally predicted by a closed-form Sharpe-MSE decoupling proposition we derive in Section 3.6 under non-zero return skewness. (H3) Lo-MacKinlay variance ratio tests show top-tier coins are indistinguishable from a random walk (|z| <= 1.5 at q is an element of {2, 5, 10}), while mid- and long-tail tiers reject the random-walk null at q = 2 (z = -2.36, z = -2.60). The findings extend across two robustness layers. An AR(1)-GARCH(1,1) baseline produces R2 approximate to -0.005 on every tier and is indistinguishable from Lasso, supporting the bias-variance bound; Giacomini-White conditional predictive ability tests reject equal predictive ability between Lasso and tree-based models on every coin in every tier, complicating naive DM interpretations; and a forward-walking 2026-Q1 holdout-83 daily observations per coin entirely outside the training window-confirms that H1 is even more decisively null on unseen data and that the H3 efficiency conclusion holds. Together, these results give a formally tested EMH-style picture for daily crypto: no model meaningfully forecasts log-returns; statistical accuracy and trading P&L are decoupled by an analytically derived mechanism; and weak-form efficiency is approximately satisfied in most liquid coins and in the convergence across the cross-section.

Computer science has become a central discipline shaping technological innovation, economic development, and participation in contemporary digital societies. Despite its growing importance, female students remain significantly underrepresented in computer science education, particularly during secondary school, when academic specialization and career trajectories begin to take shape. This article provides a social-psychological analysis of the psychological, cultural, and social factors influencing female students’ participation in computer science. Drawing on research in STEM education and social psychology, the article examines the roles of self-efficacy, gender stereotypes, sense of belonging, parental expectations, and educational climate in shaping girls’ academic aspirations. The analysis suggests that female underrepresentation in computer science cannot be explained solely by differences in ability; rather, it emerges from the interaction of individual beliefs and broader sociocultural structures. Understanding these processes is essential for developing educational strategies that promote gender equality and broaden participation in computer science education.

Metacognition is widely recognized as a powerful driver of academic performance, yet this review argues that such a performance-centred framing overlooks a second, equally consequential dimension of the construct. Building on foundational work from Flavell, Brown, Schraw and Dennison, and Efklides' MASRL, the review advances the idea that metacognition may also function as a protective psychological factor, one that helps learners navigate stress, maintain emotional stability, and sustain well-being when academic demands intensify. By examining academic achievement and subjective well-being as parallel outcomes of the same regulatory-affective system, the analysis highlights a striking imbalance: achievement research rarely considers this protective role, while well-being research engages it only partially and with limited evidence for younger learners. As a result, metacognition's buffering function remains theoretically compelling but empirically under-tested. Closing this gap requires research that measures achievement and well-being together, within the same children, during the developmental period when metacognitive and affective regulation are still taking shape.