Journal International Review of Research Studies
Journal International Review of Research Studies (JIRRS) – ISSN 3086-3600 The Journal International Review of Research Studies (JIRRS) is a peer-reviewed, open-access international scientific journal dedicated to the publication and global dissemination of high-impact research in technology, artificial intelligence, health sciences, public health, innovation, and experimental research. The JIRRS serves as a multidisciplinary platform connecting researchers, data scientists, healthcare professionals, engineers, and innovation leaders worldwide. The journal prioritizes original research articles, experimental studies, applied technological developments, AI-driven methodologies, public health analytics, and interdisciplinary scientific advances that contribute to evidence-based solutions for contemporary global challenges. JIRRS emphasizes: Artificial Intelligence in healthcare and public health systems Data science, machine learning, and predictive modeling Technological innovation and digital transformation Experimental research and applied sciences Health policy, epidemiology, and population health analytics Engineering solutions for biomedical and public health contexts The journal operates under rigorous peer-review standards, ensuring methodological robustness, ethical research conduct, statistical validation, and reproducibility of findings. Through its open-access publishing model, JIRRS promotes transparency, scientific integrity, and the democratization of knowledge, facilitating worldwide accessibility and citation impact. The Journal International Review of Research Studies (JIRRS) is published by the Unified Journals Network (UJN), United Kingdom, which is responsible for editorial governance, digital infrastructure, indexing strategy, long-term publication continuity, and international research visibility. By integrating advanced digital publishing technologies and supporting innovative experimental frameworks, JIRRS positions itself as a global reference journal for technology-driven research, AI applications in health, and interdisciplinary scientific innovation.
EDDY CURRENT SEPARATION IN NON-FERROUS METAL RECYCLING: MECHANISMS, DESIGN LIMITS, AND INDUSTRIAL SCALE-UP CONSTRAINTS — A CRITICAL REVIEW
Eddy Current Separation (ECS) is widely used in recycling flowsheets to recover non-ferrous metals, particularly from municipal solid waste, electronic waste, and metallurgical residues, where increasing regulatory pressure and circular economy targets demand higher material efficiency. This review critically evaluates the physical principles, equipment design, and operational performance of ECS, with an emphasis on interactions among particle properties (size, shape, conductivity), rotor configuration, and process conditions. While laboratory and pilot studies often report high separation efficiencies (>90% for coarse aluminum fractions), industrial performance is frequently constrained by particle heterogeneity, fines generation (<5 mm), and complex feed compositions, leading to significant losses and misclassification. The review identifies key gaps, including the lack of predictive models for multi-material streams, insufficient integration with upstream comminution and downstream sorting technologies, and limited techno-economic assessments. Particular attention is given to scale-up limitations, rotor wear, energy consumption, and the trade-off between recovery and purity. The analysis highlights that ECS should not be treated as a standalone solution but as a tightly coupled unit within integrated recycling systems. Industrial implications include the need for hybrid separation strategies and improved process control to enhance recovery of fine and complex fractions.
Eddy current separation; non-ferrous metals; recycling; particle size effects; separation efficiency; circular economy.
Copyright (c) 2026 Antonio Clareti Pereira (Author) https://creativecommons.org/licenses/by-nc/4.0
PATHOGENESIS, PATHOPHYSIOLOGY AND MANAGEMENT OF RHEUMATOID ARTHRITIS
Rheumatoid arthritis is characterised by inflammation leading to irreversible destruction of the joints, and it is connected with considerable morbidity, mortality and health related costs. Current research reveals the pervasive influence of environmental factors on the disease’s severity and activity. The pain and joint deformity are often associated with disability, depressive symptoms, a negative impact on social relationships and poorer health related quality of life. Key to more successful outcomes in chronic disease are effective selfmanagement strategies, particularly as long-term conditions. The treatment of patients with rheumatoid arthritis aims to relieve pain and to control inflammation, and the final goal is to achieve remission or at least low disease activity for all patients. The interaction between what the body experiences externally and how it reacts internally increases the variance in predictors for disease activity and complicates the understanding of the pathogenesis of rheumatoid arthritis. As new research and information regarding the biological and environmental factors that impact the disease become available, a better understanding and appreciation for the chronic, and sometimes invisible, effects of rheumatoid arthritis are likely to emanate.
Copyright (c) 2026 ADEBANKE OPEMIPO ADEYEMI, OGOKE VICTOR IKECHUKWU OGOKE, Daniel Akintayo, Adetayo Olaniyi Adeniran (Author) https://creativecommons.org/licenses/by-nc/4.0
THE EDUCATOR IN THE 21ST CENTURY: NEW CHALLENGES, EMERGING PARADIGMS, AND RECONFIGURATIONS OF TEACHING PRACTICE
This article analyzes the challenges and emerging paradigms that reconfigure teaching practice in the 21st century, considering the cultural, technological, cognitive, and institutional transformations that strain the relationships among teachers, students, knowledge, and the school. The aim is to critically discuss how such transformations affect the contemporary classroom, student profiles, the pedagogical use of digital technologies and generative artificial intelligence, pedagogical authority, and teacher education, considering the objective working conditions in which educators operate. Methodologically, the study adopts a qualitative critical narrative review, based on structured searches in the SciELO, Scopus, Web of Science, ERIC, and CAPES Periodicals Portal databases, with a time frame from 1984 to 2010 for seminal works and from 2014 to 2026 for specific literature on digital culture, platformization, and artificial intelligence in education, complemented by consultation of Brazilian and international normative documents and official reports (BNCC, BNC-Formação, Cetic.br, INEP, UNESCO). The study is positioned as an analysis centered on the Brazilian educational context, aiming to dialogue with international debates. It is argued that the 21st-century educator operates under an unprecedented configuration of demands, marked by the need to act as a critical mediator of knowledge in environments characterized by attention fragmentation, platformization of learning, and intensification of institutional pressures. Theoretical-interpretive propositions sustain that effective educational transformation requires, more than tool adoption, pedagogical intentionality, professional recognition, adequate infrastructure, and institutional commitment to meaningful learning, equity, and integral formation.
teacher education; educational technologies; artificial intelligence in education; pedagogical practice; teacher professionalism.
Copyright (c) 2026 Joelson Lopes da Paixão, Ana Cristina Tomasini, Leonardo Corrêa Costa, Wender Antônio Nunes da Silva, Gilberto Rodrigues da Silva (Author) https://creativecommons.org/licenses/by-nc/4.0
IMPACT OF INFORMATION AND COMMUNICATION TECHNOLOGIESON THE PERFORMANCE OF NIGERIAN PRINT MEDIA OPERATIONS
The study aimed to determine the impact of ICTs on the performance of Nigerian newspapers and magazines in carrying out their functions. The study employed the survey research method using questionnaire and interview, and Binary Logistic Regression was used to test the hypothesis. It was revealed that the use of ICT forms has significant impact on the performance of journalists in the Nigerian print media.The dominant ICT forms in use by print journalists undeniably impact on the operations of the print media in the areas of in-depth and speedy coverage of events, improved picture quality, wider readership and circulation as well as more advertising revenue.
ICT, Media, Nigeria, Operations, Performance, Print
Copyright (c) 2026 Gabriel Tivlumun Nyitse (Author) https://creativecommons.org/licenses/by-nc/4.0
University–School Integration as a Strategy for Scientific Literacy: Experimental Assessment of Protein Content in School Milk Using a Low-Cost Method
This study reports an interdisciplinary educational intervention designed to promote scientific literacy through the integration of public school students into a university laboratory environment. Eighth-grade students from a municipal public school in Fortaleza, Brazil, participated in an immersive scientific experience at the Experimental Biology Center of the University of Fortaleza, where they conducted an experimental activity to assess the protein content of milk provided in the school feeding program. The methodology was based on acid-induced protein precipitation using acetic acid (commercial vinegar), enabling visualization and comparative evaluation of protein presence through casein coagulation. The approach combined biochemical principles with an accessible and low-cost experimental design suitable for educational contexts. The activity allowed students to engage directly with the scientific method, including hypothesis formulation, experimentation, and interpretation of results, while also critically reflecting on the nutritional quality of their daily food intake. The findings demonstrated that the proposed strategy effectively fostered student engagement, contextual understanding of scientific concepts, and awareness of the relationship between nutrition and health. This study highlights the relevance of integrating basic education with academic scientific environments as a means of strengthening scientific literacy, promoting social awareness, and expanding access to meaningful science education experiences.
Scientific literacy; Experiential learning; Protein quantification; Milk analysis; Nutritional assessment
Copyright (c) 2026 Antonio Eufrásio Vieira-Neto, Natália Chaves Gondim Vieira (Author) https://creativecommons.org/licenses/by-nc/4.0
REIMAGINING EKITI INDIGENOUS KNOWLEDGE SYSTEM IN THE 21ST CENTURY THROUGH DIGITAL MEDIA
This study demonstrates that the indigenous knowledge systems of pre-colonial Ekiti were complex, adaptive, and deeply embedded in social, political, and ecological contexts. Far from being primitive or obsolete, these systems provided effective frameworks for governance, agriculture, healthcare, education, and conflict resolution. Colonialism and Westernisation marginalised Ekiti indigenous knowledge, weakening its transmission and institutional legitimacy. Nevertheless, the study finds that indigenous knowledge remains highly relevant to contemporary development challenges. Reimagining Ekiti indigenous knowledge through digital media offers a viable pathway for preservation, revitalisation, and integration into modern society. Digital documentation can safeguard endangered knowledge, enhance cultural continuity, and promote intergenerational transmission. Incorporating indigenous knowledge into education, policy, and development planning can contribute to sustainable development and epistemic justice. Ultimately, recognising and revitalising Ekiti indigenous knowledge affirms cultural identity and enriches global knowledge systems in the twenty-first century.
Decolonisation of knowledge, Digital heritage, Ekiti division, Indigenous knowledge systems, Yoruba history
Copyright (c) 2026 Ibidun Bolatito Opeoluwa (Author) https://creativecommons.org/licenses/by-nc/4.0
INFLUENCE OF ONLINE REVIEWS ON CUSTOMER SATISFACTION IN E-COMMERCE LOGISTICS FIRM: EVIDENCE FROM TEMU NIGERIA
The e-logistics industry is faced with increasing competition, and as a result, the companies in this industry are creating an online presence for sales maximization. By consulting social media and review websites, customers have more alternatives to consider during choice-making decisions. This study develops a multifaceted model to recognize the influence of service quality and e-word of mouth on customer satisfaction and the impact of customer satisfaction on word of mouth. Data were gathered from one hundred and fifty (150) customers of TEMU in Nigeria through a non-probability sampling technique. The participants were customers who have patronized TEMU and provided feedback on the products purchased. Structural Equation Modeling (SEM) was employed to analyze the collected data and test the proposed hypotheses. The findings indicate that service quality dimensions and e-WOM have positive effects on customer satisfaction. Furthermore, this study reinforces that customer satisfaction has a positive influence on customers’ WOM intentions. It was recommended in the study that the management of TEMU Nigeria should either integrate transportation (for last-mile delivery) into their service or list out available couriers on the delivery page for customers to select to enhance timely delivery of ordered products. The organization should explore the benefits of service quality factors and social media channels to meet and exceed customers’ expectations in order to bolster the quality of services and boost customer satisfaction, attract new customers, and retain existing customers.
Customer satisfaction, E-word of mouth, Online reviews, Service quality, Word of mouth
Copyright (c) 2026 Adetayo Olaniyi ADENIRAN , Goodness OLALEYE , Ayobami Abdulmateen GBADEGESIN (Author) https://creativecommons.org/licenses/by-nc/4.0
GREEN PRACTICES, GUEST SATISFACTION AND LOYALTY IN THE HOTEL INDUSTRY
This study examines the nexus between green activities and guests’ satisfaction, repurchase intention, and willingness to promote the hotel through good word-of-mouth (WOM). The study was hinged on Engel-Kollat-Blackwell (EKB) theory which was used to explain marketing and decision-making processes of customers when purchasing. Structured questionnaire was used to elicit information from guests staying in 2, 3, and 4-star hotels in Osun state, Nigeria, and this was achieved based on the quantitative research technique and survey research design to compare the proposed hypotheses. The results revealed a positive association between green practices and customer satisfaction, which gives a numerical evidence to affirm the influence of environmental measures, both direct and mediated through satisfaction, on the repurchase intention and the Word of Mouth that emanated from the guests. Furthermore, the association between hotel “green practices” and customer satisfaction is moderated by trip purpose. To satisfy the customer demands and achieve positive intention to repurchase, emphasis was laid on how crucial it is for hotel businesses to adopt sustainable practices.
Green practices, Satisfaction, Trip purpose, Willingness to repurchase, Word of Mouth
Copyright (c) 2026 Adetayo ADENIRAN , Esther BAMISE , Ayobami GBADEGESIN , Felix OLOYEDE (Author) https://creativecommons.org/licenses/by-nc/4.0
ARTIFICIAL INTELLIGENCE AND SCHOOL ASSESSMENT:FORMATIVE POTENTIAL, TEACHER MEDIATION, AND ETHICALCHALLENGES IN CONTEMPORARY EVALUATIVE PRACTICES
The incorporation of artificial intelligence (AI) into educational systems has expanded the possibilities for monitoring learning, producing feedback, and personalizing instruction. In school assessment, however, the adoption of these technologies requires more precise conceptual distinctions between different AI paradigms and a critical analysis of their pedagogical and ethical effects. This study aims to analyze the impacts of AI on school assessment processes by examining its formative potential, epistemological limits, and the ethical challenges involved in its use. Methodologically, this is a qualitative bibliographic study with an analytical and interpretive orientation. Rather than presenting itself as an exhaustive systematic review, the study explicitly adopts the format of an analytical bibliographic review, organized around academic literature and institutional documents relevant to the topic. The analysis is guided by the articulation between formative assessment theory and a critical sociotechnical reading of educational datafication. The study shows that the effects of AI on assessment are not homogeneous: rule-based systems tend to operate better in structured tasks; models supported by learning analytics and educational data mining expand monitoring and diagnostic capacity; and generative systems open new possibilities for open-ended tasks, but still show instability, opacity, and a persistent need for human oversight. The article concludes that AI can contribute to more continuous, responsive, and formative assessment practices, provided that its use remains subordinated to teachers' pedagogical judgment, data protection, algorithmic transparency, and principles of equity.
Inteligência artificial. Avaliação escolar. Tecnologia educacional. Ética digital. Formação docente.
Copyright (c) 2026 Joelson Lopes da Paixão (Author) https://creativecommons.org/licenses/by-nc/4.0
THE FEDERATIVE PACT AND MUNICIPAL PUBLIC POLICIES: COOPERATION, DECENTRALIZATION, AND EDUCATION FINANCING
The main objective of this work is to investigate the level of cooperation, decentralization, and dialogue that exists between municipalities due to the federal pact. The 1988 Federal Constitution established the federal pact with a peculiarity: the so-called triune federalism, which recognizes the existence of three federative entities: the Union, the states, and the municipalities. Municipalities possess their own political, administrative, and financial competencies, but this decentralization also entails serious problems. Municipalities are autonomous, but many of them do not produce enough to sustain and develop themselves, and often municipal, state, and federal responsibilities are confused with the implementation of the National Education System. By the end of 2025, this scenario had changed, with the creation of a clear document outlining what each entity should do. This was linked to the new Fund for the Maintenance and Development of Basic Education and the Enhancement of Education Professionals, officially made permanent in 2020, and the mass participation in Education Development Arrangements and municipal public consortia, which led to a significant improvement in the Basic Education Development Index of several municipalities. From a methodological point of view, a Bibliographic and Documentary Review was used, this being a quantitative-qualitative research, of a basic nature and of a theoretical genre. The main results show that cooperation between municipalities is indispensable for public policies to take place and achieve their objectives based on the federative pact, since, as demonstrated; many municipalities have improved in development, especially regarding economies of scale applied to education.
Copyright (c) 2026 Prof. Dr. Antonio Roberto Xavier, GILSON ADÃO DOMINGOS VIEIRA, Fidel Cambundo Sanuca, Edmilson Alberto Matamba, Maria Alexandrina Da Silva da Luz, Karla Renata de Aguiar Muniz, Antenor Teixeira de Almeida Junior, Layer Leorne Mendes Júnior (Author) https://creativecommons.org/licenses/by-nc/4.0
DATA STORYTELLING IN INTELLIGENT ANALYTICS SYSTEMS: FROM VISUALIZATION TO DECISION INTELLIGENCE
Abstract The widespread organizational adoption of business intelligence and analytics systems has not resolved a persistent structural problem: the gap between the availability of analytical information and its effective use in decision-making. Research documents that information overload, insufficient narrative context, and poor communicative design in conventional dashboards systematically prevent decision-makers from deriving actionable insights from available data, with consequences measurable in decision quality, cognitive load, and organizational analytics effectiveness. This article examines data storytelling — the structured integration of data analysis, visual representation, and narrative architecture to convey analytical insights in a form that supports comprehension, interpretation, and organizational action — as a theoretical and practical response to this problem. The study is positioned as an analytical-conceptual inquiry adopting an interpretivist-pragmatist epistemological orientation. It draws on an analytically structured five-stage pipeline applied to literature identified across ACM Digital Library, IEEE Xplore, Web of Science, and Scopus, covering the period from 2000 to early 2026. The theoretical framework integrates Cognitive Load Theory, Dual Process Theory, Sensemaking Theory, and Situated Cognition Theory to explain the cognitive and organizational mechanisms through which narrative structures enhance analytical communication — and to identify the theoretical tensions between these frameworks that define the boundary conditions of data storytelling's effectiveness. The article presents four paradigmatic case studies — covering industrial analytics, public health dashboard failures during the COVID-19 pandemic, marketing analytics composite performance measurement, and documented instances of narrative-induced misinterpretation — that ground the theoretical propositions in empirically documented outcomes. A five-layer Decision-Oriented Data Storytelling Framework is proposed and formally evaluated, comprising Data Foundation, Analytical Processing, Visual Abstraction, Narrative Structuring, and Decision Activation layers, each grounded in peer-reviewed empirical literature and associated with explicit evaluation criteria, criterion-evidence mappings, and boundary conditions. The framework is explicitly distinguished from existing models in the field — including the Segel and Heer narrative visualization spectrum, the S-DIKW framework, and the three-stage authoring model — and its contributions are positioned in relation to those frameworks. The article further examines the organizational, ethical, and governance implications of emerging technologies — including automated natural language generation, conversational business intelligence systems, AI copilots for analytics, and large language model-based narrative generation — and identifies the principal unresolved challenges these technologies pose for narrative integrity, decision accountability, and responsible organizational deployment. The findings support the conclusion that the transformation of dashboards from passive monitoring tools into active decision-support systems requires deliberate narrative design grounded in cognitive theory, empirical evidence, and explicit governance frameworks — and that the effectiveness of data storytelling is situationally contingent rather than universally guaranteed, varying systematically with organizational context, task complexity, audience literacy, and the integrity of the narrative structures employed. Keywords: data storytelling; narrative visualization; decision support systems; business intelligence; cognitive load theory; dashboard design; analytical communication; sensemaking; information overload; AI-assisted analytics; natural language generation; decision intelligence; visualization rhetoric; organizational analytics; data literacy
data storytelling; narrative visualization; decision support systems; business intelligence; cognitive load theory; dashboard design; analytical communication; sensemaking; information overload; AI-assisted analytics; natural language generation; decision intelligence; visualization rhetoric; organizational analytics; data literacy
Copyright (c) 2026 Gabriel Alves Souza (Author) https://creativecommons.org/licenses/by-nc/4.0
The tension between open source and proprietary software constitutes one of the defining structural conflicts of the contemporary digital economy — a conflict that is simultaneously technical, economic, political, and philosophical. This article presents a comprehensive comparative and analytical mapping of both paradigms across their technical, economic, organizational, governance, social, and geopolitical dimensions, drawing on peer-reviewed scholarship from information systems research, political economy, organizational theory, science and technology studies, and legal analysis. The analysis traces the historical emergence of proprietary software as a commercial category following IBM's 1969 unbundling decision; the countervailing institutionalization of the free software and open source movements from 1983 onward; and the subsequent decades of competitive and collaborative interaction that have produced the hybrid landscape of the present. Across the technical domains examined — operating systems, databases, programming languages, cloud infrastructure, development tooling, artificial intelligence, and cryptographic security — the article documents a structural asymmetry: open source has achieved categorical dominance at the infrastructure layer of the digital economy, while proprietary models maintain dominance at the interface and service layers where economic and political power is concentrated. Key tensions analyzed include the free rider problem and chronic underinvestment in open source commons; the strategic commoditization logic by which large technology corporations selectively open-source components to erode competitors' proprietary advantages while retaining proprietary control at value-capturing layers; the governance risks of maintainer burnout, corporate capture, and succession failure; the emerging conflicts between regulatory frameworks — including the EU AI Act, the Cyber Resilience Act, and data protection legislation — and the open source ecosystem; and the geopolitical dimensions of digital sovereignty in which the open/proprietary choice has become a matter of national strategic policy. Six paradigmatic case studies — Linux versus Windows Server, Android's open core architecture, HashiCorp's relicensing of Terraform, the Redis and Elasticsearch licensing conflicts with Amazon Web Services, Meta's LLaMA strategy, and Kubernetes' multi-stakeholder governance — are analyzed to ground the theoretical framework in empirically documented outcomes. The article concludes that the productive question is not which model is superior in the abstract, but rather who benefits from each model, under what institutional conditions, and at which layer of the technology stack — a distributional and contextual analysis that reveals the open source versus proprietary debate to be, at its deepest level, a contest over who holds the power to define how the digital world functions.
Copyright (c) 2026 Anthony Santos Batista (Author) https://creativecommons.org/licenses/by-nc/4.0
ARTIFICIAL INTELLIGENCE IN ELECTRICAL SYSTEMS: A STRUCTURED NARRATIVE REVIEW OF FOUNDATIONS, APPLICATIONS, DIGITAL ARCHITECTURES AND CHALLENGES IN GRID MODERNIZATION
The incorporation of Artificial Intelligence (AI) into electrical systems has become one of the central drivers of energy-sector digitalization. The growing operational complexity of power networks, the integration of intermittent renewable sources, the expansion of distributed energy resources, and the need for increasingly faster decisions have strengthened the relevance of machine learning, deep learning, expert systems, and reinforcement learning methods. This article presents a structured narrative review of the foundations, applications, and limitations of AI in electrical systems, with emphasis on load and renewable generation forecasting, predictive maintenance, fault diagnosis, operational optimization, and emerging digital architectures. Rather than providing a merely descriptive overview, the study organizes the literature into analytical axes, compares methodological families in terms of objectives, data requirements, strengths, and constraints, and discusses contemporary concepts such as cyber-physical energy systems, digital twins, distributed energy resource management, and edge intelligence. The results indicate that AI expands grid observability, automation capability, and anticipation of critical events, but large-scale deployment still depends on trustworthy data, interoperability, explainability, cybersecurity, and regulatory compliance. It is concluded that AI should not be understood only as an incremental automation tool, but as a structural component of the modernization of intelligent, resilient, and decentralized power grids.
Artificial Intelligence. Electrical systems. Smart grids. Energy digitalization. Operational optimization.
NEURAL NETWORKS FOR REAL-TIME FINANCIAL FRAUD DETECTION
The accelerating digitalization of financial services has transformed fraud into a systemic global threat, with annual losses estimated at $485.6 billion in 2023 alone — losses that conventional rule-based and statistical detection methods have proven structurally incapable of containing. This article presents a narrative literature review examining how neural network architectures are redefining real-time fraud detection in financial systems. The review covers the theoretical and epistemological foundations of the field, the principal neural architectures deployed — including Multilayer Perceptrons (MLPs), Long Short-Term Memory networks (LSTMs), Convolutional Neural Networks (CNNs), Autoencoders, Graph Neural Networks (GNNs), and Transformer-based models — and the production infrastructure requirements that constrain their deployment within payment authorization pipelines operating under sub-100-millisecond latency budgets. Critical operational challenges are analyzed in depth, including concept drift, adversarial evasion attacks, class imbalance, algorithmic explainability under GDPR and LGPD regulatory frameworks, and the data privacy constraints that motivate Federated Learning and Differential Privacy approaches. Real-world implementations across credit card networks, instant payment systems — with particular attention to Brazil's PIX ecosystem — anti-money laundering operations, and insurance fraud are documented. The review concludes by mapping the research frontier, encompassing online learning, Large Language Models as fraud detection orchestrators, generative AI weaponized by fraudsters, and the long-term potential of Quantum Machine Learning. Findings indicate that while no single architecture dominates across all fraud typologies, hybrid and ensemble frameworks combining temporal, relational, and anomaly-detection capabilities consistently achieve superior performance, and that the integration of regulatory compliance, explainability, and adversarial robustness alongside predictive accuracy represents the defining challenge for the next generation of production fraud detection systems.
Copyright (c) 2026 Deborah Natany Otoni Oliveira (Author) https://creativecommons.org/licenses/by-nc/4.0
Machine Learning (ML) models are developed at an unprecedented scale, yet only a fraction ever reach production — and among those that do, many fail within months. This article examines the organizational, technical, and cultural factors that prevent ML models from being successfully operationalized, and presents structured practices to address them. Through a narrative bibliographic review drawing on peer-reviewed literature and technical documentation from recognized industry organizations, the article maps seven primary barriers to ML deployment: misalignment between data science and engineering teams, data quality and governance failures, lack of reproducibility, absence of robust testing, inadequate infrastructure, neglected monitoring, and organizational resistance. As a response to these challenges, MLOps — the convergence of Machine Learning, DevOps, and Data Engineering — emerges as a systematic framework for treating models as products rather than experiments. The article describes the full ML model lifecycle in production, surveys the current tooling ecosystem, and outlines practical strategies for building an MLOps culture incrementally, regardless of organizational size. Real-world cases, including Spotify's large-scale ML platform and lessons from the regulated financial sector, illustrate how structured operationalization practices translate into measurable business outcomes. The findings suggest that the primary determinant of ML success in production is not algorithmic sophistication, but the organizational and engineering discipline surrounding model deployment, monitoring, and continuous improvement.
machine learning operations; MLOps; model deployment; technical debt; data drift; reproducibility; ML lifecycle; experiment tracking; model monitoring; LLMOps.
Copyright (c) 2026 Otávio Otávio Luís Pinheiro Oliveira (Author) https://creativecommons.org/licenses/by-nc/4.0
The elastomechanical properties of concrete expanded with aluminum nano-inclusions.
In recent years, nano-inclusion-reinforced concrete has gotten a lot of attention. Researchers have persistently examined the mechanical properties of concrete containing these inclusions. The aim of this research is to ascertain the mechanical properties of concrete augmented with nano-inclusions derived from aluminum waste.The Mori–Tanaka model is the method of homogenization used in this study. It is a common model for composites with spherical inclusions. The results show that the mechanical properties, such as the elastic modulus, shear modulus, and bulk modulus, are consistently getting better.This method gives experimental researchers a way to predict the acceptable volume fractions that can be added to concrete. This makes experiments more efficient and cuts down on unnecessary testing. To keep people safe, the maximum volume fraction is set at 30%.
Nano-inclusions, Aluminum waste, Reinforced concrete, Mori–Tanaka model, Mechanical properties
Copyright (c) 2026 Abdelmoutalib Benfrid (Author) https://creativecommons.org/licenses/by-nc/4.0
Tokens as Computational Units in Data Science and Machine Learning: Mathematical Foundations, Transformer Architecture, Inference Economy, and Caching Systems in Foundational Models
The concept of the "token" has evolved from a simple linguistic unit to a fundamental computational primitive that underpins the architecture, performance, and economics of modern artificial intelligence systems. This paper provides a comprehensive and in-depth analysis of tokens as computational units across Data Science and Machine Learning, with a particular focus on Transformer-based foundational models. We begin by tracing the evolution of tokenization from classical Natural Language Processing (NLP) to its sophisticated forms in deep learning, examining its mathematical representation through high-dimensional vectors (embeddings) and the computational complexities arising from attention mechanisms, which scale quadratically (O(n²)) with sequence length. The article then explores the economic dimension of tokens, analyzing the "token economy" that governs API-based access to large language models (LLMs) and the resulting drive for inference optimization. A significant portion of this work is dedicated to a detailed investigation of advanced caching architectures—including KV Cache, prefix caching, semantic caching, and distributed inference caching—that are critical for mitigating latency and computational costs. Furthermore, we discuss emerging trends such as token pruning, sparse attention, and long-context optimization, which are pushing the boundaries of model efficiency and capability. The paper culminates in the proposal of an original conceptual framework, the Token Efficiency Index (TEI), a novel metric designed to provide a standardized measure for evaluating the computational and economic efficiency of tokenization strategies and model architectures. This work synthesizes mathematical theory, architectural insights, and economic analysis to offer a holistic, token-centric perspective on the current state and future directions of large-scale AI.
Copyright (c) 2026 Pedro Emílio Amador Salomão (Author) https://creativecommons.org/licenses/by-nc/4.0
HUMAN RIGHTS AND DECENT WORK: ANALYSIS OF CONTEMPORARY CHALLENGES TO ENDING FORCED LABOUR
This manuscript aims to analyse the inclusion of human rights in the context of decent work. To this end, the current challenges to achieving the end of all forms of forced or compulsory labour were analysed. The Federal Constitution has human dignity as one of its pillars, considering work to be a social and fundamental right of all. The research was developed using qualitative methods, based on theoretical and methodological approaches of an exploratory, bibliographic and documentary nature. However, data analysis was carried out using the socio-legal method, as it sought to analyse international human rights treaties at work, in view of the current challenges to their implementation in the Brazilian socio-economic context. The results show that Brazil has recently implemented public policies to eradicate all forms of contemporary forced or compulsory labour. In this sense, the approval of Decree No. 12,857/2026, which internalised Protocol 2014 relating to ILO Convention No. 29, demonstrates the Brazilian government's commitment to the eradication and prevention of all forms of forced or compulsory labour, in particular slave and child labour, providing for the reparation of damages suffered by victims and the conviction of those responsible. It can be concluded that, although international instruments have been internalised, the United Nations still faces complex challenges in eradicating all forms of forced or compulsory labour, and it is incumbent upon the public authorities and society in general to ensure the effectiveness of humane and dignified work and, in accordance with SDG 8, to promote full and decent employment and sustained and sustainable economic growth for all.
Federal Constitution, Sustainable Development, Dignity of the human person, International Human Rights, Social Rights.
Davi José Nicaretta Boufleuher Davi José Nicaretta Boufleuher
Tiago Fernando Hansel Tiago Fernando Hansel
Marcela Abbado Neres Marcela Abbado Neres
BRUNA MICHELE WEIRICH LUNKES BRUNA MICHELE WEIRICH LUNKES
Copyright (c) 2026 SAMUEL FELIPE WEIRICH, Davi José Nicaretta Boufleuher, Dr. Tiago Fernando Hansel, Dra. Marcela Abbado Neres, Dr. Alvori Ahlert, BRUNA MICHELE WEIRICH LUNKES (Author) https://creativecommons.org/licenses/by-nc/4.0
The Role of Game Engines in the Democratization of Digital Game Development
Game engines have become a central element in the contemporary digital game industry, significantly contributing to the democratization of game development. By providing integrated tools, reusable systems, and accessible development environments, game engines have reduced technical and financial barriers that previously restricted game creation to large studios with substantial resources. This article examines the historical evolution of game engines, from proprietary solutions to modern, accessible platforms, and analyzes their role in enabling independent and small-scale development. Through a comparative and bibliographic methodology, the study discusses the main features of leading engines, their economic and market impacts, and their influence on the growth of the indie game sector. Additionally, the article addresses current limitations and challenges, such as technological dependence, licensing changes, and market saturation, while also exploring future trends, including open-source engines, artificial intelligence integration, and the standardization of development pipelines. The findings indicate that game engines have played a decisive role in expanding creative participation, fostering innovation, and reshaping the global game development ecosystem.
game engines; democratization of development; indie games; digital game industry; game development tools.
Copyright (c) 2026 Gabriel Pereira Costa (Author) https://creativecommons.org/licenses/by-nc/4.0
Mixed Steel Deck Systems and Their Applications in Civil Construction: A Comprehensive Review
Composite steel–concrete systems have significantly transformed structural engineering practices over the last decades. Among these systems, the steel deck slab—also known as composite slab or collaborative slab—has become one of the most efficient solutions for multi-story buildings and industrial structures. This review article presents a comprehensive analysis of the historical development, structural behavior, design principles, execution methods, advantages, limitations, economic impact, sustainability aspects, fire resistance considerations, and maintenance requirements of steel deck systems. The study consolidates technical literature, Brazilian standards (NBR 8800 and NBR 6118), and international research to evaluate the structural efficiency and practical applications of composite slabs. Results demonstrate that steel deck systems provide substantial improvements in construction speed, reduction of material waste, enhanced productivity, and optimized structural performance when compared to conventional reinforced concrete slabs. Despite certain limitations in corrosive environments and fire exposure conditions, the steel deck system represents a rational, economical, and sustainable solution for modern construction demands.
Composite slab; Steel deck; Mixed structures; Steel–concrete systems; Construction productivity; Structural efficiency.
Copyright (c) 2026 Larissa Tatiane Gonçalves de Paula (Author) https://creativecommons.org/licenses/by-nc/4.0
The Potential Of Living Concrete As A Sustainable Alternative For Regenerating Structures Exposed To Aggressive Environments: A Comprehensive Review
Concrete is one of the most widely used construction materials worldwide; however, it is highly susceptible to cracking and long-term deterioration caused by mechanical stress, environmental exposure, and chemical aggression. Structural cracks compromise durability, permeability resistance, and reinforcement protection, resulting in costly maintenance interventions. Living concrete, also known as bio-concrete or self-healing concrete, has emerged as a promising biotechnological innovation capable of autonomously repairing cracks through biologically induced calcium carbonate precipitation. This review presents a comprehensive analysis of the mechanisms, preparation methods, chemical processes, mechanical performance, sustainability aspects, advantages, limitations, and current applications of living concrete. The study consolidates experimental evidence demonstrating improved compressive strength, flexural resistance, reduced permeability, and enhanced durability compared to conventional concrete. Although higher initial costs remain a barrier, long-term economic and environmental benefits suggest that living concrete represents a transformative technology for resilient infrastructure.
Living concrete; Self-healing concrete; Biomineralization; Calcium carbonate precipitation; Sustainable construction; Structural durability.
Copyright (c) 2026 Alexandre Viera Silva Pinheiro (Author) https://creativecommons.org/licenses/by-nc/4.0
Structural Order–Disorder Effects and Photoluminescence Behavior in Aluminum-Doped CaCu₃Ti₄O₁₂: A Comprehensive Review
Calcium copper titanate (CaCu₃Ti₄O₁₂ – CCTO) has attracted significant attention due to its remarkable dielectric, optical, and photoluminescent properties. In particular, structural disorder at short and medium range has been strongly correlated with visible photoluminescence (PL) emission at room temperature. This review discusses the structural, vibrational, optical, and electronic modifications induced by aluminum doping in CCTO, emphasizing the role of order–disorder transitions, cluster formation ([TiO₆], [TiO₅], and [AlO₆]), oxygen vacancies, and band gap modulation. Special attention is given to thermal evolution between 300 °C and 800 °C, where coexistence between amorphous and crystalline domains leads to maximum PL intensity. Spectroscopic evidence from XRD, FT-IR, Raman, UV–Vis, and photoluminescence analyses is critically interpreted to establish correlations between local structural rearrangements and electronic transitions. The review consolidates experimental findings and theoretical interpretations, highlighting aluminum as an electron acceptor dopant capable of modifying defect density and tuning optical gap energies.
Copyright (c) 2026 Everson Ferreira Junior (Author) https://creativecommons.org/licenses/by-nc/4.0
A Comprehensive Review on the Comparison Between Plasterboard (Drywall) Systems and Conventional Brick Masonry in Building Construction
The construction industry has undergone significant technological transformations aimed at improving productivity, reducing costs, and increasing sustainability. Among these innovations, plasterboard (drywall) systems have emerged as an alternative to conventional brick masonry for vertical partitions. This review article presents a comprehensive comparative analysis between plasterboard systems and traditional brick masonry, focusing on structural performance, economic viability, construction speed, environmental impact, thermal and acoustic behavior, durability, and practical application in the Brazilian context. The study synthesizes technical literature, normative standards, and cost analyses to evaluate the advantages and limitations of both systems. Results indicate that while conventional masonry remains widely used due to its mechanical resistance and cultural acceptance, plasterboard systems offer significant benefits in terms of construction speed, reduced structural load, material efficiency, and design flexibility. The review concludes that the selection between systems should consider project-specific requirements, environmental conditions, and cost–benefit analysis, rather than relying solely on traditional practices.
construction systems; plasterboard; drywall; brick masonry; building materials; cost–benefit analysis.
Enhanced Visible Photoluminescence in Niobium-Doped CaCu₃Ti₄O₁₂ Perovskite Synthesized by a Soft Chemical Route
CaCu₃Ti₄O₁₂ (CCTO) perovskite oxides have been extensively studied due to their unusual dielectric, electrical and optical properties. In recent years, increasing attention has been directed toward their photoluminescent behavior, particularly in the visible region, motivated by potential applications in light-emitting devices. This review summarizes and critically discusses the current state of knowledge on photoluminescence in CCTO-based materials, with emphasis on the role of structural order–disorder phenomena, defect chemistry and donor doping, especially with niobium (Nb⁵⁺). The relationships between synthesis methods, thermal treatment, local coordination environments and electronic structure are examined. Special attention is given to the formation of localized electronic states associated with mixed TiO₆/TiO₅ coordination and oxygen vacancies, which are key factors governing visible light emission. The review highlights how controlled structural disorder and donor doping can be used as effective strategies to enhance photoluminescence at relatively low processing temperatures, reinforcing the technological relevance of CCTO-based perovskites for visible light-emitting applications.
CaCu₃Ti₄O₁₂; photoluminescence; perovskite oxides; structural disorder; donor doping; light-emitting materials.
Copyright (c) 2026 Pedro Emílio Amador Salomão, Francisco Moura Filho (Author) https://creativecommons.org/licenses/by-nc/4.0