This article presents a comparative analysis of financial literacy, focusing on educational and psychological aspects, between Brazil and the Czech Republic. Utilizing a qualitative content analysis of existing literature and sociodemographic data, the study highlights distinct contextual factors influencing financial literacy levels and behaviors in both countries. Key findings reveal differences in educational strategies, levels of financial anxiety, self-efficacy, and locus of control, contributing to a nuanced understanding of financial literacy development. The research underscores the importance of tailored educational interventions and psychological support to enhance financial well-being in diverse cultural and economic settings.

This paper examines the Kremlin’s international propaganda efforts since Russia’s full-scale invasion of Ukraine, taking Brazil as a case study for such a purpose. Based on a qualitative review of scholarly articles, book chapters, media-monitoring reports and selected journalistic investigations on Brazil, Latin America and the broader Global South, the study proceeds in three steps. First, it identifies the structural factors that make Brazil an attractive target for Kremlin influence. Second, it maps the principal dissemination channels through which Russian narratives are circulated in Brazil. Third, it identifies the most common pro-Kremlin messages spread in the Brazilian information ecosystem. The paper argues that Russian influence in Brazil works heavily through the adaptation of the Kremlin’s narratives to pre-existing Brazilian political dispositions and media vulnerabilities. Brazil is a relevant target within the Kremlin’s renewed propaganda efforts directed to the Global South because it is Russia’s main trade partner in Latin America, a fellow founding BRICS member, as well as an aspiring regional leader whose traditional political and diplomatic discourse puts significant emphasis on pragmatic neutrality, negotiated conflict management, and seeking a greater voice for non-Western states in the global order. In this environment, Kremlin narratives have circulated either directly through Russian state-funded outlets such as RT and Sputnik, or indirectly through quotation and republication by domestic media actors. The most recurrent messages cast NATO and the United States as the real agents of escalation, promote pressure on Ukraine to make concessions for achieving peace, and depict Russia as a defender of a fairer multipolar order. The paper concludes that the Brazilian case illustrates a broader pattern of Russian outreach to the Global South in which pro-Kremlin narratives tend to gain traction particularly when they can attach themselves to existing grievances, political identities, and symbolic repertoires through their recontextualization inside local debates and adaptation to domestic themes.

This study examines the invisibilization of Palestinian female humanitarian workers within humanitarian contexts, focusing on the gap between their lived agency and their representation in global academic and media discourses. Adopting a qualitative approach, the research employs the Critical Discourse Analysis (CDA) alongside the case study of paramedic Razan al-Najjar, intending to investigate how the intersection of gender, nationality, and religion shapes the international portrayal of Palestinian women’s agency. The findings suggest that, despite Palestinian women’s active involvement in humanitarian action, their roles are frequently reframed through discourses of vulnerability and victimhood, which obscure their professional and political agency. This research argues that such invisibilization reflects power imbalances and calls for a rethinking of humanitarian visibility in global discourse.

The development of porous aluminium oxides is of great interest for applications in catalysts, adsorbents, and thermal coatings due their high surface area and thermal stability. This study aimed to synthesize porous aluminium Oxide (Al2O3) anostructures using polystyrene (PS) nanospheres as a porogenic agent, via chemical precipitation was characterized bybXRD, FTIR, TGA, and field-emisssion scanning electron microscopy (FE-SEM). The diffraction patters indicated the formation of transition alumina with crystallite sizes of approximately 4nm.

The recent enactment of the Brazilian Tax Reform through Constitutional Amendment N.° 132/2023 represents a fundamental step toward aligning the national tax system with global standards, particularly the European Value Added Tax model. This domestic institutional modernization coincides with the strategic signing of the 2022 Double Taxation Convention between Brazil and the United Kingdom. International double taxation arises when the domestic laws of two sovereign States apply simultaneously to the same taxpayer, which creates significant barriers to cross-border trade and capital flow. Tracing its theoretical origins back to the 1928 Model Conventions of the League of Nations, this paper examines the 2022 convention’s structural convergence with the Organisation for Economic Co-operation and Development Model Tax Convention. By adopting a Law and Economics perspective, the study highlights how standardized international conventions reduce transaction costs and foster a stable institutional environment. Furthermore, the analysis explores how the bilateral convention addresses modern corporate complexities, emphasizing the critical role of fiscal transparency and the concept of beneficial ownership in preventing treaty shopping within the Brazil-UK economic axis. The study also discusses the integration of the new Brazilian Transfer Pricing Law, which adopts the Arm’s Length Principle to ensure international consistency. While the agreement establishes a robust framework for taxes on income and capital, the paper acknowledges that specialized areas such as cross-border inheritances and donations remain subject to unilateral legislation due to distinct administrative challenges. Ultimately, the study concludes that the convention, supported by sweeping domestic tax reform, provides the essential legal certainty required to integrate Brazil more deeply into the United Kingdom's economic sphere and secure long-term bilateral investments.

The increasing integration of digital technologies in industrial and organizational environments has intensified the need to align innovation in quality management with human-centric design principles. In this context, this study analyze the development, current status, and emerging trends in the academic literature on digitalization and innovation in quality management from a human-centric perspective. A systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, including the stages of identification, screening, eligibility, and inclusion. Scientific publications were retrieved from the Scopus and Web of Science databases. The screening and selection process was supported by the Rayyan platform, resulting in a final sample of 20 relevant studies. To complement the systematic review, bibliometric network analyses were performed using VOSviewer software, adopting a micro-level approach to explore relationships among authors, keywords, and cited references. The bibliometric visualization enabled the identification of the most influential publications, key thematic clusters, and the intellectual structure of the research field. The results highlight the growing relevance of digital technologies such as Industry 4.0 and 5.0 tools, virtual environments, and human-cyber-physical systems in the design and improvement of quality management practices. Furthermore, the findings reveal a strong connection between user experience, worker interaction with digital systems, and innovation processes within manufacturing and service contexts. The study contributes to the understanding of how human-centric principles are being integrated into digital quality management research and provides insights for both academics and practitioners interested in designing more effective and human-oriented innovation strategies. Finally, directions for future research are discussed, particularly regarding the integration of emerging digital technologies and the measurement of human experience in quality-driven systems.

As neurotechnology transitions to the commercial mainstream, electroencephalography (EEG) has emerged as a robust biometric identifier. This targeted review investigates the convergence of Deep Learning, 5G-IoT infrastructure, and Neurorights to assess the security of consumer-grade EEG biometrics. By triangulating findings across neuroscience, cybersecurity, and law, this study identifies a "Privacy Paradox": while Spatial-Temporal Transformers and Deep Neural Networks achieve identification accuracies of up to 100% across diverse mental states, the reliance on portable wearables introduces critical vulnerabilities. The analysis reveals that industries like neuromarketing frequently harvest sensitive neural data without robust encryption or an understanding of its biometric permanence. This creates a "legacy data risk" where involuntary collection leads to irreversible identity theft and subconscious intrusion via "brain-spyware." Furthermore, we examine the trade-offs between 5G latency and the computational overhead of encryption, finding that commercial deployments often prioritize user experience over data integrity. We conclude by proposing a "Neuro-Secure" framework, advocating for hardware-level encryption, edge computing, and the international adoption of Neurorights to protect cognitive liberty against the unprecedented threats posed by unregulated BCI proliferation.

Artificial intelligence (AI) has increased its influence in educational practices, particularly in the teaching of English as a Second Language (ESL). This literature review examines how AI technologies impact ESL teaching and learning in a critical manner, with an emphasis on both pedagogical benefits and emerging risks. Based on a qualitative analysis of peer-reviewed studies published between 2015 and 2024, this paper synthesizes research on intelligent tutoring systems, conversational agents, automated feedback tools, and adaptive learning platforms. The findings indicate that AI can enhance personalization, immediacy of feedback, learner autonomy, and access to resources. However, the literature also reveals significant concerns, including the erosion of human-mediated interaction, potential deskilling of learners, algorithmic bias, and limitations in pragmatic and sociocultural competence development. This review argues that the effectiveness of AI in ESL contexts depends less on the technology itself and more on its pedagogical integration. Rather than positioning AI as a substitute for teachers, this study advocates for a critical, human-centered approach in which AI functions as a scaffold that supports, but does not replace, meaningful interaction and reflective learning. The paper concludes by highlighting the need for ethically grounded and pedagogically informed implementations of AI in language education.

The following article was based on field research regarding the situations experienced by a group of seventy women which speaks to their insertion and permanence in the labor market [1]. Taking it as a basis, it is possible to state that the data collected and transformed into statistics, as well as the private testimonies of the participants, function as a powerful means for establishing connections between the selected involvements and the thoughts of authors such as Stuart Hall, Karl Marx, Fernando Coronil and Silvia Federici, who will have their ideas addressed here as a way of establishing a link between pieces of information such as the situations of exploitation, disrespect, abuse and discrimination suffered by women within and outside of employment environments and the issue of forming their identities and consequently adapting in a world that presents them with great hostility against their human persons, in addition to the constant process of degradation to which they are subjected, due to the structuring of the capitalist system and its dissemination to the four corners of the planet, paved on patriarchal values and strengthened in the West. In view of what has been presented, the main objective is to expose the nuances of these correlations in order to promote greater clarity regarding the aforementioned problems and bring light to the universalization of the truths experienced by the female group.

Employee turnover represents a critical operational and financial challenge for contemporary organizations, resulting in disrupted business processes, high replacement costs, and the depletion of institutional knowledge. While traditional statistical methods have historically supported Human Resource Management (HRM), they often fail to capture the complex, non-linear relationships inherent in human behavioral data. Recently, Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized predictive HR analytics. However, the adoption of complex algorithms is hindered by the "black box" phenomenon and the ethical risks of algorithmic bias. This study presents an expanded systematic literature review, guided by the PRISMA protocol, to evaluate the intersection of ML, employee attrition, and Explainable AI (XAI). Synthesizing empirical findings from extensive peer-reviewed literature, the results demonstrate that ensemble learning models—particularly eXtreme Gradient Boosting (XGBoost) and Random Forest—consistently achieve superior predictive performance (AUC > 0.90) when combined with data balancing techniques like SMOTE. Crucially, the integration of SHAP (SHapley Additive exPlanations) resolves model opacity by quantifying the magnitude and direction of key attrition drivers, such as excessive overtime, commute distance, and compensation disparities, while highlighting age-specific nuances in turnover behaviors. Furthermore, the review addresses the dual impact of AI on Diversity, Equity, and Inclusion (DEI), emphasizing the necessity of HR Algorithmic Bias Management Capability (HABMC) to mitigate data, model, and deployment biases. Ultimately, this paper proposes a human-in-the-loop framework, ensuring that AI-augmented HRM remains transparent, equitable, and strategically effective.

The COVID-19 pandemic significantly intensified rates of anxiety, depression, and post-traumatic stress disorder (PTSD) among children and adolescents in Brazil, compounding pre-existing gaps in public mental health policy. This narrative literature review examines the historical trajectory of child and adolescent mental health care in Brazil, assesses the psychological impacts of the pandemic on young populations, and evaluates the applicability of Artificial Intelligence (AI) as a complementary tool for expanding psychiatric care. A search of the Google Scholar database, using the Publish or Perish software, identified an initial corpus of 42 titles, from which 18 peer-reviewed articles met the defined eligibility criteria. Findings indicate that AI-driven tools, including Natural Language Processing systems and chatbots such as Woebot, demonstrate measurable efficacy in reducing depressive and anxious symptoms, improving patient monitoring, and broadening access to psychoeducation. However, their integration into public health frameworks raises significant ethical considerations regarding data privacy, algorithmic bias, and the vulnerabilities of minors. It is argued that these technologies should serve as a complement to human-led psychiatric care, and that their adoption must be guided by a robust regulatory and ethical framework suited to the Brazilian context.

Digital platforms, software and social media apps have become essential tools for important aspects of daily life, such as communication and access to services and education. However, many interfaces are still designed based on standardized assumptions about attention, perception and interaction, not considering how neurodivergent people interact and understand different aspects of design elements. This study explores how inclusive graphic and interface design can improve accessibility for neurodivergent users by conducting a literature review based on design theory and international accessibility guidelines. During analysis, the findings indicate that common barriers to these users include visual overload, inconsistent navigation, poor readability, limited personalization and distracting motion. Research indicates that practical strategies to minimize stressful interface interactions such as clear visual hierarchy, consistent navigation and user-controlled interface settings benefit not only neurodivergent and disabled users, but also the general population. In conclusion, the study finds that inclusive and human-centered design should be part of the standardized design process of all digital interfaces.

This article addresses the fragmentation and redundancy commonly found in existing classification systems related to death related cultural heritage. Many current approaches rely on extensive indexes or isolated typologies, limiting analytical navigation and relational understanding of funerary and mortuary phenomena. In response, this study proposes the development of a more comprehensive and less redundant taxonomy for thanatological heritage, encompassing both tangible and intangible dimensions. The research is based on a structured literature review of classification models, taxonomies, typologies, inventories, glossaries, and lexicons addressing funerary practices, mortuary institutions, and cultural conceptions of death. The methodological process combines iterative keyword based searches, dynamic text corpus formation, and comparative analysis of existing frameworks, supported by manual extraction and filtering of relevant concepts. UNESCO’s cultural heritage classification framework was employed as a structural reference to organize the selected elements into a coherent taxonomic system. The main result is a preliminary yet extensive taxonomy that hierarchically organizes funerary and mortuary heritage into tangible and intangible categories, further subdivided into objects, practices, belief systems, experiences, institutions, and research domains. The findings indicate that a taxonomic structure provides clearer navigation, reduced redundancy, and greater analytical usability than index based listings. The article concludes that, although intentionally general and subject to future revision, the proposed taxonomy establishes a solid foundation for further refinement and for broader theoretical discussions within museology and thanatological studies.

Globalization has intensified cultural diversity and increased the circulation of educational ideas across different countries. In this context, intercultural education has been widely promoted as an approach to foster inclusion, dialogue, and mutual understanding in diverse societies. However, despite its global relevance, its implementation varies significantly across contexts. This paper aims to analyze how intercultural education, as a globally promoted educational idea, is interpreted and applied in different contexts, highlighting the role of policy transfer and the importance of contextual factors. The study is based on a qualitative literature review of selected academic works in the fields of intercultural, comparative, and international education. The analysis focuses on how educational ideas circulate globally and how they are adapted at the local level. The findings show that, although there is a shared global discourse around intercultural education and related educational frameworks, their implementation is shaped by social, cultural, political, and institutional conditions. As a result, similar policies may lead to different outcomes depending on the context in which they are applied. In addition, the study highlights that policy transfer is not a neutral process, but involves active interpretation and adaptation by local actors. The paper concludes that comparative and international education plays a key role in understanding these dynamics, as it emphasizes the importance of context in explaining differences between global educational discourses and local practices. These findings suggest the need for more context-sensitive approaches to the development and implementation of educational policies.

Continuous-variable quantum key distribution (CV-QKD) has emerged as a promising alternative for secure communications in the post-quantum era due to its compatibility with standard telecommunication technologies. However, its practical deployment is strongly limited by the computational burden of post-processing, particularly in the privacy amplification stage. This work presents a critical literature review of privacy amplification in CV-QKD, focusing on computational scalability constraints, especially throughput and memory usage. The review was conducted through searches in Web of Science, Google Scholar, and IEEE Xplore, prioritizing studies that address privacy amplification from an implementation perspective, including large input block sizes, computational acceleration, and long-distance transmission constraints. The surveyed literature shows that most existing implementations rely on Toeplitz-based universal hashing combined with FFT-based methods, GPU acceleration, FPGA parallelism, or integrated high-speed architectures in order to improve throughput and increase the achievable secret key rate. Alternative approaches, such as stream-based privacy amplification, joint information reconciliation–privacy amplification pipelines, and LFSR-based Toeplitz constructions, have also been proposed to reduce latency, computational complexity, or storage requirements. Nevertheless, the analysis indicates that the dominant trend in the literature is to frame privacy amplification primarily as a throughput optimization problem. At the same time, finite-size security requirements force the use of increasingly large input blocks as transmission distance grows, reaching orders of 10^8, 10^9, and 10^10 bits for approximately 50 km, 80 km, and 100 km, respectively. As a consequence, memory usage remains a persistent limitation even in optimized implementations. This review therefore argues that, although memory-related constraints are widely acknowledged, they have received less systematic treatment than throughput optimization and should be more explicitly considered in the design and evaluation of scalable privacy amplification schemes for practical long-distance CV-QKD systems.